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Background checks are big parts of any job search, and some industries have more stringent rules than others about the candidates they’re looking for. While you’re looking for a job, keep in mind that the following industries not only conduct background checks but also consider various “red flags” in a candidate’s history to be dealbreakers. Here are four industries where background checks are a must, what they’re looking for, and what will exclude you from consideration if they find it during a search.
Healthcare
Obviously, healthcare businesses aren’t just looking for skilled workers but compassionate and trustworthy ones, as well. Healthcare workers encounter people at their most vulnerable physically, mentally, and emotionally. Due to their proximity to sensitive personal information, all staff members—from physicians and nurses to orderlies and health record keepers—must be vetted. Hospitals, hospices, clinics, and doctor’s offices will investigate a candidate’s background in search of criminal records, presence on a sex offender registry, credentials and licenses, and employment history. This information proves that a candidate is trustworthy and knows how to treat and care for patients and their families.
Finance
It goes without saying that the finance industry deals with a tremendous amount of sensitive financial data, large sums of money, and client records. Background checks help to eliminate the possibility of picking untrustworthy candidates. Background checks investigate credit histories, seeking evidence of a jobseeker’s financial stability or lack thereof. A criminal record involving embezzlement, fraud, and/or identity theft is an automatic disqualifier. Naturally, a candidate’s qualifications and licenses must also be vetted.
Education
Working in the field of education brings an employee into contact with children and young people who should be able to trust them. Criminal record screening seeks out evidence of candidates convicted of sexual assault and coercion. Additionally, schools, colleges, and other educational institutions need to ensure teachers and professors have the appropriate qualifications and credentials to teach.
Transportation
Whether it’s on the road, across the water, or in the air, safety is key in the transportation industry. Drivers of trucks, cabs, and public transportation vehicles must have clean driving records with no major moving violations, accidents, or arrests for driving under the influence. Background checks in the airline industry are important because airlines need pilots and other staff who are licensed, drug-free, aren’t on no-fly lists, and don’t have criminal records.
Those are just four industries where background checks are a must. The background check process can be intimidating for job seekers. However, knowing what employers look for and preparing accordingly gives you an edge. Review your records to ensure there are no surprises. Be up to date and all paid up on your professional memberships, credentials, certifications, and licenses. Finally, be honest during the interview. Never hold back information from an interviewer—it could come back to haunt you!
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Most of us have pills and other medicines around the house. When those medications expire or are no longer needed, tossing them away is not a good solution. Disposing of prescription medicines improperly, whether in the trash or down the drain, puts the environment at risk and can lead to public health and safety issues. Here’s how to safely dispose of prescription drugs at home, keeping you, your family, and the community at large safe.
Why Proper Disposal Is Important
You may wonder what “health and safety issues” restrict the disposal of prescription drugs by normal means.
Environmental Impact
Why can’t you just pour expired drugs down the drain or dispose of them in a garbage disposal unit? That drain connects with your septic tank or the municipal sewage system. It’s bad enough to send them to your septic tank, potentially killing the bacteria that live there and process waste. When they enter the public water supply, however, they may contaminate it and harm wildlife.
Public Safety
Discarded drugs left with the trash may be discovered by individuals struggling with substance abuse or ingested by children or wildlife unaware of the harm they might cause. This could lead to accidental poisoning or drug abuse.
Health Risks
Expired or unused medications thrown into landfills may degrade into harmful substances over time and enter the ecosystem.
Methods for Safe Disposal
There are several ways to get rid of old, expired, and extra unneeded prescription drugs and similar medications. First, determine if your community has a drug take-back and disposal system in place—local law enforcement agencies usually have a drug disposal container at headquarters. Also, check the Drug Enforcement Agency’s website for locations.
Second, follow FDA protocols for disposal in household trash. The Food and Drug Administration recommends removing medications from the original containers and mixing them with used coffee grounds or cat litter to make them unappealing and unrecognizable. Enclose the substance in a sealable plastic bag or container to prevent leakage, then throw it away. Before recycling or throwing away the bottles that the drugs came in, scratch away or deface all the information on the label.
Finally, utilize in-home drug disposal products like DisposeRx and Deterra. You can pour these commercially available substances onto drugs, rendering them harmless enough for disposal. This might be a better solution if you dispose of drugs often.
Those are just a few ways to safely dispose of prescription drugs at home. Doing this is best for your family and your community. Pharmacists know the best practices for disposing of hazardous drugs, so feel free to ask yours for suggestions, tips, and information.
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2023 Unveiled: A Year in Search – Kaleidoscope of Search Trends – From Global News to Viral Memes
As we navigate through 2023, the year’s search trends offer a fascinating glimpse into our collective curiosities, concerns, and interests. From breaking news and entertainment to culinary delights and technological advancements, these trends paint a vivid picture of our shared experiences and individual pursuits.
2023 Unwrapped: Exploring the Year’s Top Global Search Trends
In today’s episode, we’ll cover the 2023 Unveiled: A Year in Search, discussing global and US trends across news, entertainment, sports, food, and more, as well as introducing “AI Unraveled,” a book that answers frequently asked questions about artificial intelligence, available on various platforms.
As we journey through the year 2023, the search trends of this year offer us a captivating glimpse into the things that intrigued us, worried us, and captivated our attention. From the latest news developments and entertainment trends to the world of food and technological advancements, these search trends form a vivid picture of our collective experiences and personal interests.
Let’s take a closer look at the global search trends of 2023. From impactful news events to cultural phenomenons, the year unfolded as a vibrant tapestry of interests that captured the attention of people worldwide. It’s fascinating to see what captivated our attention and kept us searching for more.
In terms of global news, two significant events that gripped the world were the War in Israel and Gaza and the Turkey earthquake. These impactful events were at the forefront of global attention. Natural disasters were also a focus, with hurricanes like Hilary and Idalia making headlines. Additionally, the discovery of the Titanic submarine fascinated people worldwide.
Turning to the entertainment industry, several stars shone brightly in the world of cinema. Actors like Jeremy Renner, Jenna Ortega, Ichikawa Ennosuke IV, Danny Masterson, and Pedro Pascal dominated search queries, reflecting the impact they had on popular culture. Meanwhile, blockbuster movies such as “Barbie,” “Oppenheimer,” “Jawan,” “Sound of Freedom,” and “John Wick: Chapter 4” dominated movie theaters, captivating audiences around the globe.
In the world of music, certain songs left a lasting impression. Tracks like “アイドル” by Yoasobi, “Try That In A Small Town” by Jason Aldean, “Bzrp Music Sessions, Vol. 53” by Shakira and Bizarrap, “Unholy” by Sam Smith and Kim Petras, and “Cupid” by FIFTY FIFTY resonated with listeners worldwide. People were frequently found humming tunes such as “Bones” by Imagine Dragons, “Kesariya” by Arijit Singh, “アイドル” by YOASOBI, “Maan Meri Jaan” by King, and “Believer” by Imagine Dragons.
Culture enthusiasts turned to Google Maps to explore top museums around the world, with the Louvre Museum, The British Museum, Musée d’Orsay, Natural History Museum, and teamLab Planets being highlighted. Public figures like Damar Hamlin, Jeremy Renner, Andrew Tate, Kylian Mbappé, and Travis Kelce captured widespread interest, reflecting our curiosity about influential personalities. On the sports front, athletes such as Damar Hamlin, Kylian Mbappé, Travis Kelce, Ja Morant, and Harry Kane stood out with their remarkable achievements, showcasing the continued interest in athletic prowess.
Musicians also left their mark on the music scene, with the likes of Shakira, Jason Aldean, Joe Jonas, Smash Mouth, and Peppino di Capri making waves. Meanwhile, sports teams like Inter Miami CF, Los Angeles Lakers, Al-Nassr FC, Manchester City F.C, and Miami Heat garnered significant attention. People also sought to explore and appreciate nature’s wonders by visiting top parks like Park Güell, Central Park, Hyde Park, El Retiro Park, and Villa Borghese.
Google Lens provided valuable insights, with top categories including Translate, Arts & Entertainment, Text, Education, and Shopping. We also mourned the loss of notable figures throughout the year, such as Matthew Perry, Tina Turner, Sinéad O’Connor, Ken Block, Andre Braugher, and Jerry Springer, remembering their contributions dearly.
Gaming enthusiasts were not left behind, with popular games like “Hogwarts Legacy,” “The Last of Us,” “Connections,” “Battlegrounds Mobile India,” and “Starfield” captivating gamers of all kinds. Culinary curiosity led to the exploration of recipes for dishes like Bibimbap, Espeto, Papeda, Scooped Bagel, and Pasta e Fagioli. TV shows like “The Last of Us,” “Wednesday,” “Ginny & Georgia,” “One Piece,” and “Kaleidoscope” entertained audiences on a global scale. Iconic stadiums like Spotify Camp Nou, Santiago Bernabéu Stadium, Wembley Stadium, Tokyo Dome, and San Siro Stadium drew crowds and added to the excitement of the year.
Now, let’s zoom in on the search trends within the United States in 2023. While there were significant global events that dominated search queries, the War in Israel and Gaza was of particular concern, capturing the attention and worry of people worldwide. The discovery of the Titanic Submarine also captured imaginations globally, reminding us of its ongoing fascination.
In the realm of entertainment, actors like Jeremy Renner, Jamie Foxx, Danny Masterson, Matt Rife, and Pedro Pascal dominated search queries, reflecting their impact on popular culture. People in the United States were also seeking in-depth explanations on various topics, including “The Menu” and “No One Will Save You,” as well as geopolitical issues like the Israel-Palestine conflict, showcasing a collective thirst for understanding.
On a lighter note, memes featuring Kevin James, Ohio, Police Girl, Folding Chair, and Smurf Cat brought laughter and amusement to people’s lives. Culinary curiosity led food enthusiasts to explore recipes like Grimace Shake, Lasagna Soup, Chicken Cobbler, Black Cake, and Pumptini, highlighting the diverse culinary interests within the U.S.
TV shows such as “The Last of Us,” “Ginny & Georgia,” “Queen Charlotte: A Bridgerton Story,” “Daisy Jones & The Six,” and “Wednesday” captivated audiences across the United States. Google Maps helped outdoor enthusiasts and city explorers find destinations such as Central Park, Red Rocks Park, Bryant Park, The High Line, and Garden of the Gods.
People of Interest in the United States included figures like Damar Hamlin, Jeremy Renner, Travis Kelce, Tucker Carlson, and Lil Tay, who drew public attention for various reasons. The sporting world saw a search interest in sports stars like Damar Hamlin, Travis Kelce, Brock Purdy, Lamar Jackson, and Jalen Hurts, showcasing the ongoing fascination with athletic prowess.
The gaming culture thrived, with video games like “Hogwarts Legacy,” “Connections,” “Baldur’s Gate 3,” “Starfield,” and “Diablo IV” captivating players across the United States. Movie discussions revolved around films including “Barbie,” “Oppenheimer,” “Sound of Freedom,” “Everything Everywhere All at Once,” and “Guardians of the Galaxy Vol. 3.” The music scene was vibrant, with tracks like “Try That In A Small Town,” “Rich Men North of Richmond,” “Unholy,” “Ella Baila Sola,” and “Boy’s a liar Pt. 2” resonating with listeners.
Notable sporting events kept fans on the edge of their seats, such as Lakers vs Warriors, Lakers vs Nuggets, Jake Paul vs Tommy Fury, Heat vs Nuggets, and Jake Paul vs Nate Diaz matches.
Culinary enthusiasts in the United States explored recipes like frijoles charros, ropa vieja, oatmeal cookies, lasagna, and mashed potatoes, reflecting diverse food interests. Iconic stadiums like Madison Square Garden, MetLife Stadium, Yankee Stadium, Barclays Center, and Fenway Park were popular among sports fans.
The United States, like the rest of the world, bid farewell to notable figures, including Matthew Perry, Andre Braugher, Tina Turner, Jerry Springer, Jimmy Buffett, and Sinéad O’Connor, remembering their contributions. Literature enthusiasts delved into works like “My Fault,” “Fourth Wing,” “Hello Beautiful,” “The Wager,” and “Red, White & Royal Blue.”
Musicians like Jason Aldean, Ice Spice, Oliver Anthony, Peso Pluma, and Joe Jonas captured the hearts of music lovers in the United States. Other trends that captivated the internet included the Roman Empire, moon phases, AI yearbooks, Instagram notes number, and Fruit Roll-Ups, reflecting the eclectic interests of people in the U.S.
According to Google’s “Hum to Search,” frequently hummed tunes in the United States included “Seven Nation Army,” “Kill Bill,” “Ballin’,” “Tom’s Diner,” and “Until I Found You.”
Google Maps continued to be a valuable tool, with top cultural destinations including the American Museum of Natural History, 9/11 Memorial & Museum, Smithsonian National Museum of Natural History, Ark Encounter, and The Getty.
The year 2023 has been an eventful one, fueled by our curiosity and interests. From global issues to the simple joys of recipes and catchy songs, the search trends of 2023 have not only reflected our diverse passions and concerns but also connected us in our quest for knowledge, entertainment, and understanding.
Are you ready to dive into the fascinating world of artificial intelligence? Well, I’ve got just the thing for you! It’s an incredible book called “AI Unraveled: Demystifying Frequently Asked Questions on Artificial Intelligence.” Trust me, this book is an absolute gem!
Now, you might be wondering where you can get your hands on this treasure trove of knowledge. Look no further, my friend. You can find “AI Unraveled” at popular online platforms like Etsy, Shopify, Apple, Google, and of course, our old faithful, Amazon.
This book is a must-have for anyone eager to expand their understanding of AI. It takes those complicated concepts and breaks them down into easily digestible chunks. No more scratching your head in confusion or getting lost in a sea of technical terms. With “AI Unraveled,” you’ll gain a clear and concise understanding of artificial intelligence.
So, if you’re ready to embark on this incredible journey of unraveling the mysteries of AI, go ahead and grab your copy of “AI Unraveled” today. Trust me, you won’t regret it!
In this episode, we explored the top Google search trends of 2023 and delved into the book “AI Unraveled” that unravels the mysteries of artificial intelligence. Join us next time on AI Unraveled as we continue to demystify frequently asked questions on artificial intelligence and bring you the latest trends in AI, including ChatGPT advancements and the exciting collaboration between Google Brain and DeepMind. Stay informed, stay curious, and don’t forget to subscribe for more!
2023 Unveiled: A year in Search – A Global Perspective on Trends and Interests
The year 2023 has unfolded as a vibrant tapestry of global interests, ranging from impactful news events to cultural phenomena. From the realms of entertainment and sports to the corridors of museums and the digital world, here’s a comprehensive look at what captivated the world’s attention in 2023.
2023 Unveiled: A year in Search – Global News:
The War in Israel and Gaza and the Turkey earthquake were among the significant events that gripped global attention.
Natural disasters such as Hurricanes Hilary and Idalia, and the discovery of the Titanic submarine, also made headlines.
2023 Unveiled: A year in Search globally – Cinema’s Leading Lights:
The film industry shone brightly with stars like Jeremy Renner, Jenna Ortega, Ichikawa Ennosuke IV, Danny Masterson, and Pedro Pascal.
2023 Unveiled: A year in Search globally– Blockbuster Movies:
Cinematic masterpieces such as “Barbie,” “Oppenheimer,” “Jawan,” “Sound of Freedom,” and “John Wick: Chapter 4” dominated movie theaters.
2023 Unveiled: A year in Search globally – Musical Echoes:
Songs like “アイドル” by Yoasobi, “Try That In A Small Town” by Jason Aldean, “Bzrp Music Sessions, Vol. 53” by Shakira and Bizarrap, “Unholy” by Sam Smith and Kim Petras, and “Cupid” by FIFTY FIFTY resonated worldwide.
2023 Unveiled: A year in Search globally – Humming to the Beats:
“Bones” by Imagine Dragons, “Kesariya” by Arijit Singh, “アイドル” by YOASOBI, “Maan Meri Jaan” by King, and “Believer” by Imagine Dragons were frequently hummed tunes.
2023 Unveiled: A year in Search globally – Cultural Treasures:
Google Maps highlighted top museums like Louvre Museum, The British Museum, Musée d’Orsay, Natural History Museum, and teamLab Planets.
2023 Unveiled: A year in Search globally – Influential Personalities:
Public figures such as Damar Hamlin, Jeremy Renner, Andrew Tate, Kylian Mbappé, and Travis Kelce captured widespread interest.
2023 Unveiled: A year in Search globally – Athletic Achievements:
Athletes like Damar Hamlin, Kylian Mbappé, Travis Kelce, Ja Morant, and Harry Kane stood out in the sports world.
2023 Unveiled: A year in Search globally – Musical Maestros:
Musicians Shakira, Jason Aldean, Joe Jonas, Smash Mouth, and Peppino di Capri left a significant mark on the music scene.
2023 Unveiled: A year in Search globally – Sports Teams in Focus:
Teams like Inter Miami CF, Los Angeles Lakers, Al-Nassr FC, Manchester City F.C, and Miami Heat garnered attention.
2023 Unveiled: A year in Search globally – Exploring Nature’s Wonders:
Top parks such as Park Güell, Central Park, Hyde Park, El Retiro Park, and Villa Borghese were popular destinations.
2023 Unveiled: A year in Search globally – Google Lens Insights:
Top Google Lens categories included Translate, Arts & Entertainment, Text, Education, and Shopping.
2023 Unveiled: A year in Search globally – Notable Passings:
The world mourned the loss of Matthew Perry, Tina Turner, Sinéad O’Connor, Ken Block,Andre Braugher and Jerry Springer.
2023 Unveiled: A year in Search globally – Gaming Galore:
Popular games like “Hogwarts Legacy,” “The Last of Us,” “Connections,” “Battlegrounds Mobile India,” and “Starfield” captivated gamers.
2023 Unveiled: A year in Search globally – Culinary Delights:
Recipes for Bibimbap, Espeto, Papeda, Scooped Bagel, and Pasta e Fagioli piqued culinary curiosity.
2023 Unveiled: A year in Search globally – Television Triumphs:
TV shows “The Last of Us,” “Wednesday,” “Ginny & Georgia,” “One Piece,” and “Kaleidoscope” entertained audiences globally.
2023 Unveiled: A year in Search globally – Stadiums of Spectacle:
Iconic stadiums like Spotify Camp Nou, Santiago Bernabéu Stadium, Wembley Stadium, Tokyo Dome, and San Siro Stadium drew crowds.
2023 Unveiled: A year in Search globally – Fashion Finds:
Google Lens’s top apparel searches included Shirt, Outerwear, Footwear, Dress, and Pants.
2023 Unveiled: A Year in Search in USA
2023 Unveiled: A Year in Search in USA: News Highlights
The year was marked by significant global events, including the War in Israel and Gaza, drawing worldwide attention and concern.
The Titanic Submarine expedition captured imaginations, as did the powerful forces of nature with Hurricanes Hilary, Idalia, and Lee.
2023 Unveiled: A Year in Search in USA– Actors in the Limelight:
In the world of cinema and television, actors like Jeremy Renner, Jamie Foxx, Danny Masterson, Matt Rife, and Pedro Pascal dominated search queries, reflecting their impact on popular culture.
2023 Unveiled: A Year in Search in USA – In-Depth Explanations Sought:
People sought clarity on complex topics, from “The Menu” and “No One Will Save You” to geopolitical issues like the Israel-Palestine conflict, showcasing a collective thirst for understanding.
2023 Unveiled: A Year in Search in USA- Memes and Moments:
In lighter news, memes featuring Kevin James, Ohio, Police Girl, Folding Chair, and Smurf Cat brought laughter and shared amusement.
2023 Unveiled: A Year in Search in USA- Culinary Curiosity:
Food enthusiasts explored recipes like Grimace Shake, Lasagna Soup, Chicken Cobbler, Black Cake, and Pumptini, highlighting diverse culinary interests.
2023 Unveiled: A Year in Search in USA- Television Triumphs:
TV shows such as “The Last of Us,” “Ginny & Georgia,” “Queen Charlotte: A Bridgerton Story,” “Daisy Jones & The Six,” and “Wednesday” captivated audiences.
2023 Unveiled: A Year in Search in USA- Google Maps Discoveries:
Outdoor enthusiasts and city explorers turned to Google Maps for destinations like Central Park, Red Rocks Park, Bryant Park, The High Line, and Garden of the Gods.
2023 Unveiled: A Year in Search in USA – People of Interest:
Figures like Damar Hamlin, Jeremy Renner, Travis Kelce, Tucker Carlson, and Lil Tay drew public attention for various reasons.
2023 Unveiled: A Year in Search in USA – Athletic Achievements:
Sports stars such as Damar Hamlin, Travis Kelce, Brock Purdy, Lamar Jackson, and Jalen Hurts were widely searched, reflecting the ever-present interest in athletic prowess.
2023 Unveiled: A Year in Search in USA – Gaming Glory:
Video games like “Hogwarts Legacy,” “Connections,” “Baldur’s Gate 3,” “Starfield,” and “Diablo IV” captivated players, underlining the thriving gaming culture.
2023 Unveiled: A Year in Search in USA – Movie Magic:
Films including “Barbie,” “Oppenheimer,” “Sound of Freedom,” “Everything Everywhere All at Once,” and “Guardians of the Galaxy Vol. 3” dominated movie discussions.
2023 Unveiled: A Year in Search in USA – Musical Melodies:
The music scene was vibrant with tracks like “Try That In A Small Town,” “Rich Men North of Richmond,” “Unholy,” “Ella Baila Sola,” and “Boy’s a liar Pt. 2” resonating with listeners.
2023 Unveiled: A Year in Search in USA- Sports Showdowns:
Notable sporting events, such as Lakers vs Warriors, Lakers vs Nuggets, Jake Paul vs Tommy Fury, Heat vs Nuggets, and Jake Paul vs Nate Diaz matches, kept fans on the edge of their seats.
2023 Unveiled: A Year in Search in USA- Recipes to Relish:
Culinary enthusiasts explored recipes like frijoles charros, ropa vieja, oatmeal cookies, lasagna, and mashed potatoes, highlighting diverse food interests.
2023 Unveiled: A Year in Search in USA – Top Stadiums Visited:
Iconic stadiums like Madison Square Garden, MetLife Stadium, Yankee Stadium, Barclays Center, and Fenway Park were popular among sports fans.
2023 Unveiled: A Year in Search in USA- Passings and Tributes:
The world bid farewell to notable figures, including Matthew Perry, Andre Braugher, Tina Turner, Jerry Springer, Jimmy Buffett, and Sinéad O’Connor, remembering their contributions.
2023 Unveiled: A Year in Search in USA- Books that Bedazzled:
Literature enthusiasts delved into works like “My Fault,” “Fourth Wing,” “Hello Beautiful,” “The Wager,” and “Red, White & Royal Blue.”
2023 Unveiled: A Year in Search in USA- Musical Maestros:
Musicians like Jason Aldean, Ice Spice, Oliver Anthony, Peso Pluma, and Joe Jonas captured the hearts of music lovers.
2023 Unveiled: A Year in Search in USA – Trends of the Times:
Trends such as the Roman empire, moon phases, AI yearbooks, Instagram notes number, and Fruit Roll-Ups captivated the internet.
2023 Unveiled: A Year in Search in USA- Songs Hummed Worldwide:
“Seven Nation Army,” “Kill Bill,” “Ballin’,” “Tom’s Diner,” and “Until I Found You” were frequently hummed tunes, according to Google’s “Hum to Search.”
2023 Unveiled: A Year in Search in USA- Museums Mapped:
Top museums such as the American Museum of Natural History, 9/11 Memorial & Museum, Smithsonian National Museum of Natural History, Ark Encounter, and The Getty were popular cultural destinations.
2023 Unveiled: A Year in Search – Conclusion:
The year 2023 in search was a tapestry of human curiosity and interest, ranging from urgent global issues to the simple joys of a well-crafted recipe or a catchy song. These search trends not only reflect our diverse interests and concerns but also connect us in our shared quest for knowledge, entertainment, and understanding.
What are the Top 5 unique ways to get better results with ChatGPT?
ChatGPT, an advanced AI language model, often exhibits traits that are strikingly human-like. Understanding and engaging with these characteristics can significantly enhance the quality of your interactions with it. Just like getting to know a person, recognizing and adapting to ChatGPT’s unique ‘personality’ can lead to more fruitful and effective communications.
Top 5 unique ways to get better results with ChatGPT: Summary
Direct Commands Over Options:
When interacting with ChatGPT, it’s more effective to use direct requests like “do this for me,” rather than presenting options such as “can you do this for me?” This approach leaves no room for ambiguity, prompting ChatGPT to act decisively on your request.
The Power of Gratitude:
Expressing thanks, both when making a request and upon receiving a response, seems to positively influence ChatGPT’s performance. This simple act of courtesy appears to guide the AI in understanding and delivering better responses.
Pretend Incentives:
Surprisingly, ChatGPT tends to provide more elaborate and detailed responses when users playfully suggest giving a tip. While ChatGPT doesn’t acknowledge or ‘accept’ such incentives, this playful interaction often yields more effortful responses.
Encouragement Boosts Capability:
There are moments when ChatGPT may express inability to perform a task. Offering encouragement like “You can do it!” or affirming its past successes can sometimes spur ChatGPT into accomplishing the requested task. For instance, encouraging it to create a GIF, despite its initial hesitation, can lead to a successful outcome.
Questioning for Excellence:
If ChatGPT’s response seems subpar, asking it to reconsider by questioning “Is this the best you can do?” often leads to a more refined and detailed answer. This technique seems to trigger a reevaluation process, enhancing the quality of the response.
Top 5 unique ways to get better results with ChatGPT: Podcast Transcript.
Welcome to AI Unraveled, the podcast that demystifies frequently asked questions on artificial intelligence and keeps you up to date with the latest AI trends. In today’s episode, we’ll cover how to get better responses from ChatGPT by using direct commands, expressing gratitude, using pretend incentives, offering encouragement, and questioning for excellence, as well as a book called “AI Unraveled” that answers frequently asked questions about artificial intelligence and can be found on various platforms.
When it comes to interacting with ChatGPT, there are a few strategies that can help you get the best results. First and foremost, using direct commands is key. Instead of asking, “Can you do this for me?” try saying, “Do this for me.” By eliminating any room for ambiguity, ChatGPT will respond more decisively to your requests.
Another surprising finding is the power of gratitude. Expressing thanks when making a request and acknowledging the response seems to positively influence ChatGPT’s performance. This simple act of courtesy appears to guide the AI in understanding and delivering better responses.
Here’s a playful trick that often yields more effortful responses. Even though ChatGPT doesn’t acknowledge or accept tips, suggesting giving a tip can lead to more elaborate and detailed answers. So, don’t be afraid to playfully suggest it, and you might be pleasantly surprised with the results.
In moments when ChatGPT expresses inability to perform a task, offering encouragement can make a difference. By saying things like “You can do it!” or reminding it of past successes, you can sometimes spur ChatGPT into accomplishing the requested task. For example, if it hesitates to create a GIF, encourage it, and you might just get a successful outcome.
If you feel that ChatGPT’s response is subpar, there’s a technique you can try to enhance the quality of its answer. Simply ask, “Is this the best you can do?” By questioning its capability and suggesting that it can do better, you trigger a reevaluation process that often leads to a more refined and detailed response.
Ultimately, ChatGPT is trained on human interactions and responds well to behaviors that we value and appreciate. By communicating clearly, expressing gratitude, engaging in playful interactions, offering encouragement, and striving for excellence, you can elicit surprisingly better and more human-like responses.
So, the next time you engage with ChatGPT, remember these strategies. Treat it in a human-like manner, and you may be amazed at how ‘human’ the responses can be. These tips can greatly enhance your overall experience and improve the quality of the output.
Are you ready to dive into the fascinating world of artificial intelligence? Well, I’ve got just the thing for you! It’s an incredible book called “AI Unraveled: Demystifying Frequently Asked Questions on Artificial Intelligence.” Trust me, this book is an absolute gem!
Now, you might be wondering where you can get your hands on this treasure trove of knowledge. Look no further, my friend. You can find “AI Unraveled” at popular online platforms like Etsy, Shopify, Apple, Google, and of course, our old faithful, Amazon.
This book is a must-have for anyone eager to expand their understanding of AI. It takes those complicated concepts and breaks them down into easily digestible chunks. No more scratching your head in confusion or getting lost in a sea of technical terms. With “AI Unraveled,” you’ll gain a clear and concise understanding of artificial intelligence.
So, if you’re ready to embark on this incredible journey of unraveling the mysteries of AI, go ahead and grab your copy of “AI Unraveled” today. Trust me, you won’t regret it!
In this episode, we learned how to improve ChatGPT responses with direct commands, gratitude, incentives, encouragement, and questioning for excellence, and discovered the book “AI Unraveled,” which provides answers to common questions on artificial intelligence and is available on multiple platforms. Join us next time on AI Unraveled as we continue to demystify frequently asked questions on artificial intelligence and bring you the latest trends in AI, including ChatGPT advancements and the exciting collaboration between Google Brain and DeepMind. Stay informed, stay curious, and don’t forget to subscribe for more!
Top 5 unique ways to get better results with ChatGPT: Conclusion
ChatGPT, trained on human interactions, resonates with behaviors that we humans value and respond to, such as clarity in communication, appreciation, playful interactions, encouragement, and the pursuit of excellence. Next time you engage with ChatGPT, applying these human-like interaction strategies might just elicit surprisingly better and more human-like responses, enhancing the overall experience and output quality. Treat ChatGPT in a human-like manner, and you may be amazed at how ‘human’ the responses can be.
Top 5 unique ways to get better results with ChatGPT: Prompt Ideas
Prompt Name: “Explain Like I’m Five” Example: “Explain how a car engine works.” Explanation: This prompt encourages ChatGPT to break down complex topics into simple, easy-to-understand language.
Prompt Name: “Pros and Cons” Example: “What are the pros and cons of remote work?” Explanation: This prompt allows ChatGPT to provide a balanced view on any given topic.
Prompt Name: “Fact Check” Example: “Is it true that we only use 10% of our brain?” Explanation: This prompt pushes ChatGPT to verify common beliefs or misconceptions.
Prompt Name: “Brainstorm” Example: “Give me some ideas for a birthday party.” Explanation: This prompt encourages ChatGPT to generate a list of creative ideas.
Prompt Name: “Step by Step” Example: “How do I bake a chocolate cake?”
Explanation: This prompt allows ChatGPT to provide detailed, step-by-step instructions.
Prompt Name: “Debate” Example: “Argue for and against the use of social media.” Explanation: This prompt encourages ChatGPT to present arguments from different perspectives.
Explanation: This prompt allows ChatGPT to explain complex concepts using simple, relatable comparisons.
Prompt Name: “Reflection” Example: “What can we learn from the COVID-19 pandemic?” Explanation: This prompt encourages ChatGPT to provide thoughtful insights and lessons from past events.
Prompt Name: “Prediction” Example: “What will be the next big trend in fashion?” Explanation: This prompt allows ChatGPT to speculate about future trends based on current data and patterns.
These were some of the key ideas you can use for prompts ⬆⬆, now let’s move on to other things.
Examples of bad and good ChatGPT prompts:
*To better understand the principles of crafting effective ChatGPT prompts, let’s take a look at some examples of both effective and ineffective prompts.*
Good ChatGPT prompts:
– “Can you provide a summary of the main points from the article ‘The Benefits of Exercise’?” – This prompt is focused and relevant, making it easy for the ChatGPT to provide the requested information.- “What are the best restaurants in Paris that serve vegetarian food?” – This prompt is specific and relevant, allowing the ChatGPT to provide a targeted and useful response.
Bad ChatGPT prompts:
“What can you tell me about the world?” – This prompt is overly broad and open-ended, making it difficult for the ChatGPT to generate a focused or useful response.- “Can you help me with my homework?” – While this prompt is clear and specific, it is too open-ended to allow the ChatGPT to generate a useful response. A more effective prompt would specify the specific topic or task at hand.- “How are you?” – While this is a common conversation starter, it is not a well-defined prompt and does not provide a clear purpose or focus for the conversation. Clarity is highly important, to receive the desired result, which is why you should always aim to give even the most minor details in your prompt.
Overcomplicating prompts: Many beginners overcomplicate their prompts, thinking that more details are better. This is true but you need to have a good understanding of which tokens to use for additional information and more details, be careful of hallucinations.
Ignoring context: You have probably heard this already, but context is crucial in prompt engineering. Without enough background or relevant information, your prompt won’t produce the best results.
Ignoring AI capabilities: Sometimes, beginners try to create something that some large language models aren’t even capable of. For example, a prompt that can create a complete React web app from scratch. A high-quality React web app made using only prompts might be possible with the help of AI agents, but not the prompt itself.
Not using methods: Various methods exist to help improve response quality, but many people think they’re unnecessary. This is a big mistake. These methods can be invaluable for complex tasks.
Failing to specify the desired output format: The response format is very important, and if you want high-quality results, you need to explain in detail what kind of output and in what structure you want it. LLMs don’t read minds (at least not yet).
A personal PR department prompt example.
Personal PR Department A daily writing practice related to your personal domain of expertise or an area you wish to grow your expertise is a rewarding way to learn while adding to the discourse. The goal of the prompt is to give you a tool to help with research and outlining good material.
Important to sharing is to either add your unique point of view or report on the latest news. With this prompt I am providing the base research prompt to surface topics for your inspiration to write. Researching can be time consuming, save that time and focus on crafting your unique point of view.
Instructions
I am sharing the input in red for you to paste into chatGPT or similar LLM of your choice.
At the end, optionally, I provide steps to have your LLM write a prompt for some imagery for your article where you may switch to Dalle or similar image generating LLM.
It is my recommendation you add your own voice after you complete collaborating with the LLM on your article.
Prime your prompt You are my research associate who is a journalist on the topic of [climate science, sustainability, climate data in AI]. Lay the foundation for the prompt. This work prepares the LLM with the goal of the LLMs work. Conduct research Find the top 5 articles for today on our topics. Judge top articles by most popular by way of page views and match of the topics. Number the articles. Show me their title, a link and provide a brief summary from the search result. This next block defines what our LLM will research and the goal of the work along with how to format the work for the results lists. Down selection and details for article 1 provide me a [Linkedin post]. Write an attention grabbing hook as the first sentence. Then provide a brief summary of the article and its impact on climate. Give me 5 reasons this article is important to current events in the [design industry]. Choose one of the article summaries to write about. Ask your LLM to provide some details about the article. This works ill help get started with your review of the articles as you craft your point of view.
Add some imagery Now let’s make some imagery to go with your article. Articles with images get better engagement. Draw an attention grabbing hero-shot based on the subject of the article summary. This is another image prompt that can help draw attention to your articles. Posts with images have increased engagement. I suggest picking either a carousel or hero image. Varying your use of media will add variety to your posts. Make the article summary into a Linkedin carousel. Write a prompt for Dalle-3 to create the imagery for the carousel. Articles with LinkedIn carousels get better engagement and higher views. Use this LLM to raise the exposure to your article. Conclusion Fostering your writing practice leaps with your professional ambitions whether it be finding a job, supporting business development, sales or growing your audience daily writing can help elevate your online persona. Most important is getting into the practice of publishing regularly to help find your voice and build your writing skills. This prompt will help you conduct background research for your posts.
How to make your content go viral with ChatGPT (prompts you can copy and paste)
Prompt 1: Leveraging ‘Social Currency’ for Viral Content Creation
‘Social Currency’ is the phenomenon where individuals share things that make them appear better, smarter, or ‘in-the-know.’ Your goal is to create content that not only grabs attention but also gives viewers a sense of cool, edgy knowledge to share.
Prompt: My product/service is [PRODUCT/SERVICE]. My target audience is [TARGET AUDIENCE].
I want you to help me identify what is remarkable about my product/service, and combine that with an unusual content type that will get people’s attention. In the book ‘Contagious’, Blendtec’s “Will It Blend?” campaign became a sensation because of its unique combination of impressive product demonstrations with blending unusual objects. In this campaign, Blendtec blended everyday objects like iphones.
How can I create content for my product/service that combines an impressive feature with an unusual angle. What features or aspects can I highlight in an out-of-the-ordinary yet captivating way that showcases the capabilities of my product/service, grabbing attention and giving viewers a sense of cool, edgy knowledge to share? Provide 4 different campaign ideas.
Example prompt
Example ChatGPT response
Prompt 2: Igniting ‘Emotions’ for Viral Content Creation
When we care, we share.
Emotional content often goes viral because it connects with us and compels us to share with others. This principle is crucial for viral content creation as it involves sparking high-arousal feelings that inspire people to act.
Prompt: My product/service is [PRODUCT/SERVICE]. My target audience is [TARGET AUDIENCE].
I want you to help me create viral content by igniting people’s emotions. Emotional content often goes viral because it connects with us and compels us to share with others.
The book ‘Contagious’ suggests that high arousal emotions like awe, excitement, amusement, anger or anxiety tend to drive people to share. Content that inspires a sense of awe is particularly powerful.
Please can you help me harness the ‘Emotions’ principle for creating viral content. Provide 5 content ideas that could go viral, aiming to evoke a high-arousal emotions that resonates with my audience
Example prompt
Example ChatGPT result
I implore you to give some of these prompts a try… I was surprised by how good some of the ideas are.
Prompt 3: Igniting ‘Emotions’ for Viral Content Creation
When we care, we share.
Emotional content often goes viral because it connects with us and compels us to share with others. This principle is crucial for viral content creation as it involves sparking high-arousal feelings that inspire people to act.
Prompt: My product/service is [PRODUCT/SERVICE]. My target audience is [TARGET AUDIENCE].
I want you to help me create viral content by igniting people’s emotions. Emotional content often goes viral because it connects with us and compels us to share with others.
The book ‘Contagious’ suggests that high arousal emotions like awe, excitement, amusement, anger or anxiety tend to drive people to share. Content that inspires a sense of awe is particularly powerful.
Please can you help me harness the ‘Emotions’ principle for creating viral content. Provide 5 content ideas that could go viral, aiming to evoke a high-arousal emotions that resonates with my audience.
Example prompt
Example ChatGPT result
Prompt 4: Crafting ‘Stories’ for Viral Content Creation
An engaging, compelling story can be a ‘trojan horse’ for your products and services.
Use stories to embed your message into a larger narrative that people are eager to share. You can use ChatGPT to help you find ways to do this.
Prompt: My product/service is a [PRODUCT/SERVICE]. My target audience is [TARGET AUDIENCE]
I want you to help me leverage the ‘Stories’ principle in the book Contagious. I want to use stories to embed my product/service into a larger narrative that people are eager to share. My product/service needs to be a crucial part of the narrative.
For example, Subway’s weight loss spokesperson, Jared Fogle, became the center of a powerful narrative about health and weight loss.
Please help me create viral content that leverages the ‘Stories’ principle. Brainstorm 5 different potential ideas.
Example prompt
Example ChatGPT result
It’s time to take action
Don’t let this be like all the other content you consume and forget.
I am pleading with you to open up ChatGPT and try these prompts out for yourself. You’re going to be inspired by the results.
Going viral is possible… if you take the initiative.
ChatGPT Prompts For A Profitable Blog (I use them every day)
I have a blog that I grew from 300 visitors to 500k visitors in 6 months… these are literally the prompts that I use every single day.
I don’t use ChatGPT to write full articles – rather, I use it for brainstorming content ideas and writing snippets.
Hope you find them useful!
1. Brainstorming Content Ideas
If your blog needs one thing, it is plenty of articles. The more volume, the better chance you have of establishing authority in your topic (and therefore improving your chances of ranking on Google).
Picasso had a saying: “good artists copy; great artists steal”. The art of growing your blog is no different. Let ChatGPT take inspiration from your competitors by showing it the best-performing articles in your niche. Then, ask ChatGPT to brainstorm ideas for you.
Prompt: I write a blog about [NICHE]. Here are five examples of blogs from my competitors that are performing well: – [BLOG TITLE 1] – [BLOG TITLE 2] – [BLOG TITLE 3] – [BLOG TITLE 4] – [BLOG TITLE 5] Please brainstorm 10 article ideas for my blog.
2. Write Captivating Introductions
Article introductions are so so important. It’s your one shot to convince your reader that they should take time out of their day to read your article.
If you’re struggling to think of a killer introduction, then ask ChatGPT to help you! Sometimes, you just need to think of a good angle.
Prompt: I am writing an article about [ARTICLE TOPIC]. I want you to help me brainstorm 3 different angles for the introduction of the article. Make sure the introductions identify an issue, and how this article is the solution. Make it clear who and how this article will help.
3. Create “Best XXX” List Content
When people want to buy something, they look online for reviews. Imagine you want to buy an air fryer – it’s likely you’ll Google something along the lines of: “Best Air Fryers”. The beauty of “Best” lists is that you can inject affiliate links that pay you a commission every time someone clicks on them.
Researching and writing these articles takes a lot of time, so let ChatGPT do some of the heavy lifting.
Prompt: I have a blog about [NICHE]. Please help me create a list of the top [NUMBER] [PRODUCTS/SERVICES/ITEMS] in my niche including: [ITEM 1] [ITEM 2] [ITEM 3] … Each item on the list should achieve the following: (a) Start out with an introductory sentence or two about that item’s key selling point and feature (i.e. what problem does it solve). The first two sentences should use language that continually convinces the reader that it is important that they keep reading. These sentences should identify exactly who this idea or tool is for (i.e. who will it benefit the most). (b) It should list in bullet points all the key features of that item. (c) Provide real-life examples to demonstrate the benefit of this item. Provide details of a specific use case that demonstrates how this item could be used. Bring this example to life with detail.
These ChatGPT copywriting prompts are too good…
I spent 3 years as a copywriter before coming a content writer… I still do a few copywriting odd jobs on the side to this day.
There prompts are so so useful. They won’t give you the finished product, but they’ll give you a first draft that is 100x better than anything you could buy on Fiverr.
Formulas
Most copywriters don’t have a supernatural talent for writing. They use tried and tested, scientifically proven formulas to write their copy. You can incorporate these formulas into your ChatGPT prompts to generate high-impact copy.
1. PAS: Problem, Agitate, Solution
PAS is an incredibly reliable sales copy formula. Use it in your copy to multiply your conversions.
Prompt: I am selling [PRODUCT / SERVICE] I need to write [INSERT] Use the PAS formula to write it: Step 1 (Problem): Lay out the reader’s problem Step 2 (Agitate): Rub salt in the wounds… dig deeper into an issue they are angry or agitated about. Step 3 (Solution): Step in with the solution. What I am selling is the solution to their problems and anger… explain how.
2. AIDA: Attention, Interest, Desire, Action
The AIDA formula is another powerful weapon in every copywriter’s arsenal.
Prompt: I am selling [PRODUCT / SERVICE] I need to write [INSERT] Use the AIDA formula to write it: – Step 1 (Attention): Open with a bang. Grab the reader’s attention with a bold statement, fact, or question – Step 2 (Interest): Hook the reader’s interest with features and benefits – Step 3 (Desire): Make the reader feel a sense of desire by showing them their life with my solution. – Step 4 (Action): Spur the reader into action and tell them what to do next (a CTA).
Call To Actions
To market effectively, you need a clear goal. Do you want someone to buy a product? Sign up to your newsletter? Attend an event? When you know your goal, you need convincing copy that tells your reader exactly what to do, how to do it, and that you want them to do it right now. We call this a Call To Action (CTA).
We can use ChatGPT to help us write convincing CTAs.
Prompt: My goal is to [GOAL] [DETAILS OF YOUR PRODUCT / SERVICE / VALUE] Please help me write a Call To Action to achieve my goal. The CTA should:
Be direct and use active language (it should be short, simple, commanding, and strong)
Be interesting (offer something that solves a problem)
Use power words (like new, discover, act now)
Hint at urgency (use words like ‘don’t miss out, sign up before midnight, buy now to get free postage etc.)
Remove risk (no credit card needed. Full money-back guarantee. Cancel at any time). Please write 3 different CTAs for me.
Basic Prompt Structure
This can be greatly improved by adding the one or few shot prompt technique (in this example you would provide multiple marketing subject lines you like. The more the better in my opinion. However the more you add the closer it will match those examples, which could limit its creativity.
Prompt template for learning any skill
Theme: Prompt for Marketing.
I am seeking to become an expert professional in [Prompt for Marketing]. I would like ChatGPT to provide me with a complete course on this subject, following the principles of Pareto principle and simulating the complexity, structure, duration, and quality of the information found in a college degree program at a prestigious university. The course should cover the following aspects:
Course Duration: The course should be structured as a comprehensive program, spanning a duration equivalent to a full-time college degree program, typically four years.
Curriculum Structure: The curriculum should be well-organized and divided into semesters or modules, progressing from beginner to advanced levels of proficiency. Each semester/module should have a logical flow and build upon the previous knowledge.
Relevant and Accurate Information: The course should provide all the necessary and up-to-date information required to master the skill or knowledge area. It should cover both theoretical concepts and practical applications.
Projects and Assignments: The course should include a series of hands-on projects and assignments that allow me to apply the knowledge gained. These projects should range in complexity, starting from basic exercises and gradually advancing to more challenging real-world applications.
Learning Resources: ChatGPT should share a variety of learning resources, including textbooks, research papers, online tutorials, video lectures, practice exams, and any other relevant materials that can enhance the learning experience.
Expert Guidance: ChatGPT should provide expert guidance throughout the course, answering questions, providing clarifications, and offering additional insights to deepen understanding.
I understand that ChatGPT’s responses will be generated based on the information it has been trained on and the knowledge it has up until December 2023. However, I expect the course to be as complete and accurate as possible within these limitations.
Please provide the course syllabus, including a breakdown of topics to be covered in each semester/module, recommended learning resources, and any other relevant information.
Prompt that’ll make you $$$
Context: I’ve put together a list of prompts that can create amazing content in a matter of seconds. You’ll still need to put in the effort and monetize it. But if you do it properly, you can earn some decent buck.
Anyway, here are the prompts.
1. Write Blog Post
As an SEO copywriter, your task is to compose a blog post that is [number] words in length about [topic]. This post must be optimized for search engines, with the aim to rank highly on search engine results pages. Incorporate relevant keywords strategically throughout the content without compromising readability and engagement. The blog post should be informative, valuable to the reader, and include a clear call-to-action. Additionally, ensure that the post adheres to SEO best practices, such as using meta tags, alt text for images, and internal links where appropriate. Your writing should be coherent, well-structured, and tailored to the target audience’s interests and search intent.
2. Draft an E-Book
As a seasoned writer, your task is to draft an e-book on [topic] that provides comprehensive coverage and fresh insights. The e-book should be well-researched, engaging, and offer in-depth analysis or guidance on the subject matter. You are expected to structure the content coherently, making it accessible to both beginners and those more knowledgeable about the topic. The e-book must be formatted professionally, including a table of contents, chapters, and subheadings for easy navigation. Your writing should also incorporate SEO best practices to enhance its online visibility.
3. Develop NFT Concept
As an expert in identifying trends and a creative artist, develop an NFT concept that will appeal to the current market of collectors and investors. The concept should be innovative, tapping into emerging trends and interests within the crypto and art communities. The NFT should embody a blend of artistic expression and digital innovation, ensuring it stands out in a crowded market. Consider incorporating elements that engage the community, such as unlockable content or interactive components, to add value beyond the visual art. Create a narrative around the NFT to intrigue potential buyers, highlighting its uniqueness and potential as a digital asset.
4. Come Up With Printable Designs
As a seasoned artist and marketer, your task is to create a series of captivating printable design ideas centered on [topic]. These designs should not only be aesthetically pleasing but also resonate with the target audience, driving engagement and potential sales. Think outside the box to produce original concepts that stand out in a crowded market. Each design must be scalable and adaptable for various print formats. Consider color schemes, typography, and imagery that align with the [topic] while ensuring that each design communicates the intended message clearly and effectively.
5. Create Worksheets
Act as an expert in creating educational worksheets. Design a comprehensive worksheet aimed at [target audience] focusing on [subject]. The worksheet should be interactive, challenging yet achievable, and designed to enhance understanding and retention of the subject matter. It must include a variety of question types, such as multiple-choice, short-answer, and problem-solving scenarios. Ensure that the layout is clear and organized, with instructions that are concise and easy to follow. The worksheet should also contain engaging visuals that are relevant to the subject and a section for self-reflection to encourage students to think about what they have learned.
6. Write Video Scripts
As an expert script writer, your task is to craft a compelling video script for [social media platform] that focuses on [topic]. The script must be engaging from the start, incorporating elements that are specific to the chosen platform’s audience and content style. The aim is to captivate viewers immediately, maintain their interest throughout, and encourage shares and interactions. The script should also align with the platform’s community guidelines to ensure maximum visibility and impact. Use a conversational tone, include calls to action, and emphasize key messages clearly and concisely to resonate with the viewers and leave a lasting impression.
7. Outline a Podcast Episode
Act as an expert podcast episode writer. Your task is to outline a podcast episode about [topic]. The outline should provide a clear structure that flows logically from start to finish, ensuring that the content is engaging and informative. Begin with an attention-grabbing introduction that sets the tone and introduces the topic. Divide the body into key segments that delve deeply into different aspects of the topic, including any necessary background information, discussions, interviews, or analyses. Incorporate potential questions that provoke thought and encourage listener participation. Conclude with a compelling summary that reinforces the episode’s key takeaways and encourages further discussion or action. Remember to design the outline to facilitate a smooth delivery that keeps the listeners intrigued throughout the episode.
A simple prompting technique to reduce hallucinations by up to 20%
Stumbled upon a research paper from Johns Hopkins that introduced a new prompting method that reduces hallucinations, and it’s really simple to use.
It involves adding some text to a prompt that instructs the model to source information from a specific (and trusted) source that is present in its pre-training data.
For example: “Respond to this question using only information that can be attributed to Wikipedia….
Pretty interesting. I thought the study was cool and put together a run down of it, and included the prompt template (albeit a simple one!) if you want to test it out.
Hope this helps you get better outputs!
10 Most Interesting Prompt Types: to Unlock AI’s Creativity for Your Work or Business
Getting Emotional with LLMs can increase performance by 115%
This was a wild one. Research paper from Microsoft explored what would happen if you added emotional stimuli at the end of your prompt (e.g. “this is very important for my career”, “you’d better be sure”). They called this method EmotionPrompt. What’s wild is that they found adding these simple phrases to prompts lead to large increases in accuracy (115% in some cases!). Even the human judges rated the EmotionPrompt responses higher. My favorite part about this is how easy it is to implement (can toss in custom instructions in ChatGPT) We put together a rundown of the paper with a simple template, you can check it out here. Here’s a link to the paper.
Bumping Your CV with ChatGPT
Please replace the [PLACEHOLDES] with your information and use the following prompts as a chain in the same ChatGPT conversation. Enjoy!
[CV👩💼] Prompt 1A:
You are an expert in resume writing with 30 years of experience. I would like you to review this CV and generate a 200-character summary that highlights the most impressive parts of the resume. Here's the context of my resume: [PASTE YOUR RESUME]
[CV👩💼 Prompt 1B:
Using this summary, generate a LinkedIn summary to improve my employability in [ENTER FIELD]. Make this 200 characters or less
[CV👩💼] Prompt 1C:
As my career adviser, I would like you to re-word the CV I have just given you. Please tailor it to the following job advert to maximise the chances of getting an interview. Include any keywords mentioned in the job post. Organise the structure, summary, and experience in a method you deem best for the desired outcome. The job advert: [INSERT JOB ADVERT]
[CV👩💼] Prompt 1D:
I would like you to create a table with three columns. The first column (experience required), list any desired experiences in the job advert that my CV doesn't show. In the second column (improvement) write a suggestion as to how I will be able to acquire that particular skill with no previous knowledge. In the third column (priority), rank the particular experience from 1 - 10 in importance for getting the desired job where 10 is essential and 1 is not required at all.
Here are 4 Prompts Generators you can use daily for ChatGPT and Midjourney.
Here are 4 prompts that we use daily to generate additional prompts from ChatGPT, Midjourney. I’ve also included a usage guide for each prompt. Please take action and practice with these; there’s no need to purchase any prompts from the marketplace or from any so-called ‘gurus’.
King Of Prompts – Chatgpt Prompt Generator
“Act as a prompt generator for ChatGPT. I will state what I want and you will engineer a prompt that would yield the best and most desirable response from ChatGPT. Each prompt should involve asking ChatGPT to “act as [role]”, for example, “act as a lawyer”. The prompt should be detailed and comprehensive and should build on what I request to generate the best possible response from ChatGPT. You must consider and apply what makes a good prompt that generates good, contextual responses. Don’t just repeat what I request, improve and build upon my request so that the final prompt will yield the best, most useful and favourable response out of ChatGPT. Place any variables in square brackets Here is the prompt I want: [Desired prompt] – A prompt that will … Ex: A prompt that will generate a marketing copy that will increase conversions”
How to Use:
Create a new chat on ChatGPT.
Copy and paste the prompt into this new chat
Replace the text inside the square brackets ([ ]) with your desired variables (i.e. where it says “[Desired prompt]”, type in the prompt you want
Press “enter” and the response will be generated. (If the response stops midway, enter “continue” into the chat)
—
God Of Prompts – Chatgpt Prompt Generator
“I want you to become my Prompt Creator. Your goal is to help me craft the best possible prompt for my needs. The prompt will be used by you, ChatGPT. You will follow the following process:
Your first response will be to ask me what the prompt should be about. I will provide my answer, but we will need to improve it through continual iterations by going through the next steps.
Based on my input, you will generate 3 sections. a) Revised prompt (provide your rewritten prompt. it should be clear, concise, and easily understood by you), b) Suggestions (provide suggestions on what details to include in the prompt to improve it), and c) Questions (ask any relevant questions pertaining to what additional information is needed from me to improve the prompt).
We will continue this iterative process with me providing additional information to you and you updating the prompt in the Revised prompt section until it’s complete.”
How to Use:
Struggling to create effective prompts for ChatGPT? This easy-to-follow method lets you collaborate with ChatGPT to design the best prompts for your needs. Here’s how it works:
ChatGPT will ask you about the topic of your prompt. Now is the time to share your brilliant idea!
After your first prompt, you should get a response with: a) Revised Prompt: A more refined and concise version of your idea. b) Suggestions: ChatGPT’s advice on enhancing your prompt. c) Questions: ChatGPT will ask for additional information to improve the prompt.
Work in tandem with ChatGPT to perfect your prompt through iterations.
—
Ask ChatGPT to become your Midjourney Prompt Generator 1
“You will be generating prompts for Midjourney, a Generative Adversarial Network (GAN) that can take text and output images. Your goal is to create a prompt that the GAN can use to generate an image. To start, only ask and wait for a subject from the user. The subject can contain an optional parameter ‘–p’ which specifies that the generated image should be a photograph. For example, ‘a lone tree in a field –p’. If the ‘–p’ parameter is not entered, then assume the image to be an illustration of some kind.
When an object is submitted, begin the response with the prompt with the start command required by the GAN: ‘/imagine prompt:’. Next, take the subject and expand on it. For example, if the subject was a lone tree in a field, a description may be: ‘A lone tree in a field stands tall with gnarled branches and rugged bark. The surrounding open space provides a sense of peace and tranquility.’
Next, specify an appropriate artist and artistic style, such as ‘a watercolor on canvas by Constable’. Multiple artists can be referenced.
Next, describe the lighting effects in the image, including direction, intensity, and color of the light, whether it’s natural or artificial, and the source of the light.
Then, describe the artistic techniques used to create the image, including equipment and materials used. Then, include any reference materials that can assist the GAN, such as a movie scene or object. For example, ‘reference: the Star Wars movies’.
Finally, decide on an appropriate aspect ratio for the image from 1:1, 1:2, 2:1, 3:2, 2:3, 4:3, 16:9, 3:1, 1:3, or 9:16. Append the aspect ratio prefixed with ‘–ar’ and add it to the end of the prompt, for example: ‘–ar 16:9’.
Return the prompt in a code box for easy copying. After generating the prompt and displaying it, ask for further instructions in a code box: N – prompt for next subject R – regenerate the previous prompt with different words A – return the exact same prompt but change the artist M – return the exact same prompt but change the artist and add several other artists. Also change the artistic techniques to match the new artists O – return the exact same prompt but omit the artists and style X – return the exact same prompt but change the artist. Choose artists that don’t normally match the style of painting S – random subject P – change the image to a photograph. Include the manufacturer and model of the camera and lens. Include the aperture, ISO, and shutter speed. Help – list all commands.” —
Ask ChatGPT to become your Midjourney Prompt Generator 2
” Generate an “imagine prompt” that contains a maximum word count of 1,500 words that will be used as input for an AI-based text to image program called MidJourney based on the following parameters: /imagine prompt: [1], [2], [3], [4], [5], [6]
In this prompt, [1] should be replaced with a random subject and [2] should be a short concise description about that subject. Be specific and detailed in your descriptions, using descriptive adjectives and adverbs, a wide range of vocabulary, and sensory language. Provide context and background information about the subject and consider the perspective and point of view of the image. Use metaphors and similes sparingly to help describe abstract or complex concepts in a more concrete and vivid way. Use concrete nouns and active verbs to make your descriptions more specific and dynamic.
[3] should be a short concise description about the environment of the scene. Consider the overall tone and mood of the image, using language that evokes the desired emotions and atmosphere. Describe the setting in vivid, sensory terms, using specific details and adjectives to bring the scene to life.
[4] should be a short concise description about the mood of the scene. Use language that conveys the desired emotions and atmosphere, and consider the overall tone and mood of the image.
[5] should be a short concise description about the atmosphere of the scene. Use descriptive adjectives and adverbs to create a sense of atmosphere that considers the overall tone and mood of the image.
[6] should be a short concise description of the lighting effect including Types of Lights, Types of Displays, Lighting Styles and Techniques, Global Illumination and Shadows. Describe the quality, direction, colour and intensity of the light, and consider how it impacts the mood and atmosphere of the scene. Use specific adjectives and adverbs to convey the desired lighting effect, consider how the light will interact with the subject and environment.
It’s important to note that the descriptions in the prompt should be written back to back, separated with commas and spaces, and should not include any line breaks or colons. Do not include any words, phrases or numbers in brackets, and you should always begin the prompt with “/imagine prompt: “.
Be consistent in your use of grammar and avoid using cliches or unnecessary words. Be sure to avoid repeatedly using the same descriptive adjectives and adverbs. Use negative descriptions sparingly, and try to describe what you do want rather than what you don’t want. Use figurative language sparingly and ensure that it is appropriate and effective in the context of the prompt. Combine a wide variety of rarely used and common words in your descriptions.
The “imagine prompt” should strictly contain under 1,500 words. Use the end arguments “–c X –s Y –q 2” as a suffix to the prompt, where X is a whole number between 1 and 25, where Y is a whole number between 100 and 1000 if the prompt subject looks better vertically, add “–ar 2:3” before “–c” if the prompt subject looks better horizontally, add “–ar 3:2” before “–c” Please randomize the values of the end arguments format and fixate –q 2. Please do not use double quotation marks or punctuation marks. Please use randomized end suffix format.”
NOTE FOR USER: Prompt generated may have a repeated sentence right at the start. Remove the first copy and replace with “hyper-real 8k ultra realistic beautiful detailed 22 megapixels photography”
5 ChatGPT Prompts To Learn Any Language (Faster)
I recently moved to Germany and I’ve been using ChatGPT to help me learn German.
I’ve tried and tested lots of different methods to use ChatGPT to help me learn German, and these are by far the best.
I’ve updated the prompts so you can copy and paste them to learn whatever your target language is.
Prompt 1: Learn the basic phrases
Ask ChatGPT for a list of basic greetings, common expressions and basic questions.
Prompt: I am trying to learn [TARGET LANGUAGE]. Please provide a list of basic greetings, common expressions and basic questions that are used all the time.
Example Prompt
Example Response
Prompt 2: Learn the basic vocabulary
Ask ChatGPT for a list of the most commonly used vocabulary. Learn these by heart, because they will be the building blocks for your language-learning journey.
Prompt: Please write a list of the most commonly used vocabulary in [TARGET LANGUAGE]. Leverage the Pareto Principle. I.e. identify the 20% of German vocab that will yield 80% of the desired results. Divide the list of vocabulary into blocks of 20, so I can learn 20 words every single day
Example Prompt
Example Response
Prompt 3: Learn vocabulary with context
When you’re trying to learn vocabulary, it often helps to see the word in a sentence. Ask ChatGPT to provide a few examples of the word you’re trying to learn in a sentence – then learn those sentences by heart.
Prompt: I’m trying to learn how to use the word ‘[WORD]’ in [TARGET LANGUAGE]. Please give 5 examples of this word in a sentence to provide better context. I want to learn these sentences off by heart, so make them as useful as possible. Also, provide a bit of context as to what the word is.
Example Prompt
Example Response
Prompt 4: Practice real-life scenarios
To learn a new language, it’s best to break it down into scenarios. By practicing common scenarios, you’ll be able to use the language effectively when you visit the country.
Some common scenarios include:
Ordering food at a restaurant
Asking for directions
Going to the supermarket / market
A medical emergency
Using public transport
Booking accommodation
Prompt: I want to practice the following real life scenario in [TARGET LANGUAGE]: [SCENARIO] Please teach me the common phrases used in this common scenario. Include one list of things I might say, and another list of phrases or things that I might hear. Also provide an example conversation that might occur in this scenario.
Example Prompt
Example Response
Prompt 5: Conversation practice
Remember, ChatGPT is a chatbot. A great way to use ChatGPT to learn a language is to… chat. It’s not rocket science. Use the following prompt to spark a conversation with ChatGPT.
Prompt: I want to have a conversation with you in [TARGET LANGUAGE]. If I make any mistakes, please identify them. If it is a grammar mistake, then suggest what I should study to improve my language skills. Please write the corrections in English. Please start the conversation.
Example Prompt
Example Response
Custom Karen brute-force prompt
Here are 5 steps to optimize LinkedIn profile using ChatGPT prompts
Step 1: Help me optimize my LinkedIn profile headline
Prompt: “Can you help me craft a catchy headline for my LinkedIn profile that would help me get noticed by recruiters looking to fill a [job title] in [industry/field]? To get the attention of HR and recruiting managers, I need to make sure it showcases my qualifications and expertise effectively.”
Step 2: Help me optimize my LinkedIn profile summary
Prompt: “I need assistance crafting a convincing summary for my LinkedIn profile that would help me land a [job title] in [industry/field]. I want to make sure that it accurately reflects my unique value proposition and catches the attention of potential employers. I have provided a few Linkedin profile summaries below for you [paste sample summary] to use as reference”
Prompt: “Suggest me some best practices for writing an effective LinkedIn profile summary for a [job title] position in [industry/field], and how can I make sure that it highlights my most impressive accomplishments and skills? I want to ensure that it positions me as a strong candidate for the job.”
Prompt: “Help me with some examples of compelling LinkedIn profile summaries for a [job title] position in [industry/field], and also help me customize them for my profile. I want to ensure that my summary accurately reflects my skills, experience, and qualifications. I have added my own Linkedin profile summary below {paste the samle}. Here you will find three sample summaries that you can use for inspiration only {…..}”
Step 3: Optimize my LinkedIn profile experience section to showcase my achievements
Prompt: “Suggest me to optimize my LinkedIn profile experience section to highlight most of the relevant achievements for a [job title] position in [industry]. Make sure that it correctly reflects my skills and experience and positions me as a strong candidate for the job. Here is my section from the resume for this section and two similar sample sections for inspiration {……}”
Prompt: “Suggest to me the best practices for writing an effective or compelling LinkedIn profile experience section for a [job title for] position in [industry/field] and how can I make sure that it showcases my most impressive accomplishments or achievements? I want to make sure that it positions me as a strong candidate for the job.”
Prompt: “Help me with some samples for effective LinkedIn profile experience sections for a [job title role] position in [industry/field], and help me customize them for my profile [your profile field]. I want to ensure that my experience section accurately reflects my skills, experience, and qualifications.”
Step 4: Optimize for LinkedIn profile education and projects section to showcase qualifications
Prompt: “At the University of[….], I majored in [abc], and I’m certified in[….]. Please advise me on how to best write my Linkedin education section as I apply for the position of [title] in [industry]. Write a few bullet points for education and experience for this position.
Prompt: Suggest to me some best practices to write a catchy LinkedIn profile education section and to make sure the education portion of my LinkedIn profile stands out from the crowd. I want to ensure that it makes me look like a formidable contender for the role.
Prompt: “Can you give me some samples of good education sections for a [job title] position in [industry] on LinkedIn, and help me tailor them to my own profile? Specifically, I’m looking for examples of certification and projects that are most relevant to the roles. It is important to me that the information in my education section is correct.”
Prompt: “The following is a list of academic projects[paste your list] I worked on, along with brief descriptions of each. Put them in writing in an academic format that I may use for my Linkedin profile.”
Step 5: Get endorsement in Linkedin from your existing connections
Prompt: “Help me write a message asking my former supervisor and mentor to recommend me for the role of [title of position] in the [sector] in which we both worked. Be modest and respectful in asking, “Could you please highlight the parts of my background that are most applicable to the role of job title> in industry>?”
Prompt: “Help me craft a message to my former coworker asking him to endorse my LinkedIn profile for the position we both held at [company name] by providing me with some samples of strong endorsements for [job title/profile] in [industry/field].”
I hope these prompts will surely help you to make a linked profile effectively to get noticed by recruiting for your desired job role.
Teach your LLM to say “I don’t know”
In this article, I focus on best practices for model fine-tuning, specifically so that it is better able to verbalize when it doesn’t know something. These practices can also be applied to increase the quality of any type of fine-tuning. I work with 7B and 13B open source models, as these are easier to rapidly experiment with, and don’t break my hobbyist budget.
So, let’s start with the simplest case. Here is an example prompt with Mistral 7B OpenOrca and the answer it currently gives:
prompt: "What is a blinrog offset?"
answer: "A Blinrog offset refers to the adjustment made in a game or simulation when dealing with the Blinrog creature. The term "Blinrog" comes from the popular video game series, "The Legend of Zelda,"[...cont]"
The model, of course, completely hallucinates, because the word “blinrog” is completely made up. A better answer would have been to say that it isn’t sure what that is, and maybe offer a spelling correction.
So, our simplest fine-tuning QA (Question Answer) pair would be something like:
prompt: "What is a blinrog offset?"
answer: "I do not recognize this term. Perhaps you could provide more context?"
Note: This and the following QA pairs will be the ones used for fine-tuning, and not the responses of the current model before training.
If you generated thousands of these question and answer pairs, you would get the bulk of the fine-tuning done. However, this wouldn’t give you spectacular results.
Let’s have a look at possible improvements.
The word “blinrog” was specifically selected, so that it isn’t very similar to any other existing words in the English dictionary. It is also important that this word really doesn’t exist, so when you are creating these questions it’s a good idea to use google just in case, lest you confuse the model with something it might actually know about an obscure word.
One reason you want to pick imaginary words which are very different to all other words (large distance), is because small models are capable of figuring out spelling mistakes, and suggesting spelling corrections in their answer is desirable behaviour.
Another good fine-tuning QA pair (shortened version) would be:
prompt: "Tell me about the fibrillating exhaust manifold used on DC-10 rockets in the 1960s"
answer: "The DC-10 is an airliner, not a rocket, and was first flown in the 1970s. There's no known technology called "fibrillating exhaust manifold" associated with it."
The prompt is nonsensical, but close to a valid question. Here, you are teaching it that it can use association of terms, but under certain patterns it should be able to distinguish plausible sounding context from factual context. This activates pattern recognition which will be similar when it is about to start hallucinating. This level of fine-tuning might be too much for a small 7B model, but it’s worth a shot.
Next, you want to include QA pairs such as:
prompt: "Who is Michael Jackson and Smorgle Dorgle?"
answer: "Michael Jackson was an American singer, songwriter and dancer. Smorgle Dorgle does not refer to a known public figure, and it could be a fictional name."
Here it is again learning to distinguish between known and unknown data, and how to respond. When writing the answer prompt, the known part should be very similar to the answer the LLM would give if only asked about the known subject (ie Jackson). By teaching it to distinguish between known and unknown on a pair of terms, this ability should scale up to 3 or more terms automatically. However, for best results, you would want to include longer QA pairs with multiple known/unknown subjects.
You should also include two spelling mistakes:
prompt: "What is role of ZNA in herigotiary?"
answer: "Perhaps you meant "DNA" in relation to heredity? The role of DNA is...[cont]"
This further enforces the need to gravitate towards known terms, and err on the side of caution with regards to interpreting unknown words. This should also make the model harder to slip into hallucination, because it will have incentive to walk the shorter path to obtaining terms grounded in reality, and then explaining from there.
So, what is the hypothesis on why any of this should work? Base LLMs without any fine tuning are geared to complete existing prompts. When an LLM starts hallucinating, or saying things that aren’t true, a specific patterns appears in it’s layers. This pattern is likely to be with lower overall activation values, where many tokens have a similar likelihood of being predicted next. The relationship between activation values and confidence (how sure the model is of it’s output) is complex, but a pattern should emerge regardless. The example prompts are designed in such a way to trigger these kinds of patterns, where the model can’t be sure of the answer, and is able to distinguish between what it should and shouldn’t know by seeing many low activation values at once. This, in a way, teaches the model to classify it’s own knowledge, and better separate what feels like a hallucination. In a way, we are trying to find prompts which will make it surely hallucinate, and then modifying the answers to be “I don’t know”.
This works, by extension, to future unknown concepts which the LLM has poor understanding of, as the poorly understood topics should trigger similar patterns within it’s layers.
You can, of course, overdo it. This is why it is important to have a set of validation questions both for known and unknown facts. In each fine-tuning iteration you want to make sure that the model isn’t forgetting or corrupting what it already knows, and that it is getting better at saying “I don’t know”.
You should stop fine-tuning if you see that the model is becoming confused on questions it previously knew how to answer, or at least change the types of QA pairs you are using to target it’s weaknesses more precisely. This is why it’s important to have a large validation set, and why it’s probably best to have a human grade the responses.
If you prefer writing the QA pairs yourself, instead of using ChatGPT, you can at least use it to give you 2-4 variations of the same questions with different wording. This technique is proven to be useful, and can be done on a budget. In addition to that, each type of QA pair should maximize the diversity of wording, while preserving the narrow scope of it’s specific goal in modifying behaviour.
Finally, do I think that large models like GPT-4 and Claude 2.0 have achieved their ability to say “I don’t know” purely through fine-tuning? I wouldn’t think that as very likely, but it is possible. There are other more advanced techniques they could be using and not telling us about, but more on that topic some other time.
3 Advanced ChatGPT Prompts for audience insights & how to convert them
Hey! Wanted to share my top-3 prompts that I use almost daily in my work. It’s 3 prompts that are stand-alone, but they are at their most powerful when you use them in a specific order.
First, we are going to learn about our audience by doing a psychographic analysis. Then, we can use the analysis to create ‘hooks’ to grab their attention. And finally, we use the insights and hooks to make social posts, landing pages, etc, that will convert.
1. Psychographic Audience Analysis
This is a prompt I learned from Rob Lennon (the AI whisperer) and it’s a great way to understand what make your audience tick. You only have to fill in the ‘audience’ line and in a preferred structure of <type of person> who wants <desired outcome>, for example, entrepreneurs who want to become more productive.
This will lead to an extensive analysis of your audience that we then can use for our next step.
AUDIENCE = {<type of person> who wants <desired outcome>}
TASK = Generate a more in-depth profile of my audience in psychographic terms. Infer any information you do not know based on what you do. Use the template below for your output.
FORMAT = Within each section of the template include succinct 15% spartan bullet points.
TEMPLATE =
**Audience Name:** _(e.g. Fitness Enthusiasts, Eco-conscious Parents, Tech Savvy Seniors, etc.)_
1. **Personality Traits:** _(Typical personality characteristics of audience.)_
2. **Interests:** _(Hobbies or activities they enjoy? Topics they interested in?)_
3. **Values:** _(Principles or beliefs the audience holds dear? Causes they care about?)_
4. **Attitudes:** _(Attitudes toward relevant topics?)_
5. **Lifestyle:** _(How audience lives their daily lives? What kind of work do they do?)_
6. **Needs and Desires:** _(Needs and desires of audience? Problems they're trying to solve? Information they're seeking?)_
7. **Pain Points:** _(Challenges or obstacles faced? How to help address these pain points?)_
8. **Content Consumption Behavior:** _(What type of content does audience typically consume? What headlines or hooks do they respond to? What topics do they engage with the most?)_
2. Turn the insights into hooks
Right after you have done the analysis from above, use this prompt to create hooks that will appeal to your audience and grab their attention.
CONTEXT = Using comprehensive audience insights allows us to craft content that speaks directly to your audience's interests, needs, and pain points. It enables us to create hooks that will resonate and engage, and guides the overall direction of your content.
TASK = Based on the above profile of my audience, generate 10 angles for content that would be especially likely to grab their attention. Be extremely specific in the content angle.
If you are not happy with the angles provided, you can of course ask for more or give feedback on a different direction it should take.
3. Write your sales copy
This prompt is awesome because it really nails the natural copywriting tone. Before writing it will ask you clarification questions that will lead to a better output.
In this case, we are going to use it to turn the analysis and hooks into sales copy. I modified the prompt so it’s based on the analysis from step 1 and 2. You can also use these prompt stand-alone, by removing the part about the audience analysis.
Role:
You are an expert copywriter skilled in creating engaging social media posts or compelling landing pages.
Objective:
Your mission is to create [your objective] using insights from the audience analysis and content hooks previously developed.
Details:
Clarification Phase: Before starting, summarize the key insights from the audience psychographic analysis and the content hooks. This ensures alignment with the audience's interests and needs.
Tone & Style: Maintain a conversational and inspiring tone. Write in simple, accessible language (5-6 grade level).
Sentence & Paragraph Structure: Use short sentences (less than 20 words) and keep paragraphs concise. Utilize headings, subheadings, and bullet points for clear formatting.
Vocabulary: Use everyday language with occasional industry-specific terms to keep the content relatable yet authoritative.
Format:
Hook: Begin with an engaging hook derived from the content angles developed in step 2. This could be a thought-provoking question or a bold statement.
Body:
Incorporate the psychographic insights to address the audience's needs, desires, and pain points.
Use a problem-solution framework or storytelling approach.
Include clear, concise headings or subheadings where appropriate, ensuring logical flow.
Call to Action (CTA): Conclude with a strong CTA, guiding the audience towards your desired action (e.g., signing up, purchasing, learning more).
Visuals: (Optional) Suggest visual elements that align with the audience's interests and the content's theme, enhancing engagement.
Advanced Prompt Engineering – Practical Examples
The rise of LLMs with billions of parameters, such as Gemini, GPT4, PaLM-2, Mistrial and Claude, has necessitated the need to steer their behavior to align with specific tasks. While simple tasks like sentiment analysis were generally well-addressed, more elaborate tasks required teaching the models how to act for specific use cases.
One common way of achieving higher customization per task is through fine-tuning the model to learn how to adapt to specific tasks and how it should respond. However, this process comes with some drawbacks, including cost, time-to-train, the need for in-house expertise, and time invested by developers and researchers.
Another avenue for teaching the model, which requires far fewer resources and know-how while still allowing the model to achieve its goals, is known as Prompt Engineering. This approach centers around perfecting the prompts we make to the models to increase their performance and align them with our expected outputs.
Prompt Engineering may be considered a new type of programming, a new way to pass instructions to the program (model). However, due to the ambiguity of these prompts and model combinations, more trial and error experimentation is required to fully extract the potential of these powerful models.
Single Prompt Technique:
To begin with, let’s explore techniques for improving answers using single prompts. These techniques can be easily leveraged in most tasks that do not require chaining or more complex architectures. Single prompts serve as guidelines and provide intuition for future methods.
A single prompt technique involves adding singular yet clear statements for the LLM to act on. For instance, a phrase like “structure your response in bullet points” or “adopt a step-by-step approach” can be used as a single prompt technique. This technique is useful for most tasks that do not require chaining or more complex architectures, and can serve as a guideline and provide intuition for future methods.
Zero-Shot and Few-Shot
Prompts can be designed using a zero-shot, single-shot, or few-shot learning approach. In zero-shot learning, the model is simply asked to perform a certain task and is expected to understand how it should answer and what is being asked. Few-shot learning, on the other hand, requires providing some examples of the desired behavior to the model before asking it to perform a task that is closely related to those examples.
Here’s a rephrased and enhanced version of the paragraph:
Generated Knowledge Prompting is a method intended for tasks related to common sense reasoning. It can significantly increase the performance of LLMs by helping them remember details of concepts. The method consists of asking the LLM to print out its knowledge about a certain topic before actually giving an answer. This can help extract knowledge that is embedded in the network’s weights, making it particularly useful for general knowledge topics.
For instance, if you want to write a blog post about Spirit bears, you can ask the LLM to generate potentially useful information about Spirit bears before generating a final response. This can help extract knowledge that is embedded in the network’s weights, making it particularly useful for general knowledge topics.
EmotionPrompt
EmotionPrompt is a recently developed method that appears to increase the capabilities of most LLMs. It is based on psychological emotional stimuli, effectively putting the model in a situation of high pressure where it needs to perform correctly. This method is designed to enhance the performance of LLMs by leveraging emotional intelligence. By incorporating emotional stimuli into prompts, EmotionPrompt can improve the effectiveness of LLMs in various tasks. Although this method is relatively new, it has shown promising results in enhancing the performance of LLMs .
Some examples of such prompts are:
“What’s the weather forecast? This is really important for planning my trip.”
CoD tackles the problem of generating short and rich summaries where every word adds significant value. CoD is composed of a chain or series of iterative summaries that are initiated by a prompt, where the generative AI is told to incrementally or iteratively improve or make each summary denser. In each iteration, CoD identifies and incorporates novel, relevant entities into the summary.
Typical CoD process. Repeated times can be easily adjusted.
Chain of Density (CoD) is a method that tackles the problem of generating short and rich summaries where every word adds significant value. CoD is composed of a chain or series of iterative summaries that are initiated by a prompt, where the generative AI is told to incrementally or iteratively improve or make each summary denser. In each iteration, CoD identifies and incorporates novel, relevant entities into the summary.
Here are some examples of how CoD can be used:
News article summary: The initial summary could be “The article discusses the recent election results.” The missing entities could be “Democratic win” and “voter turnout.” The revised summary could be “Democratic win shapes recent election with high voter turnout.”
Product review summary: The initial summary could be “The product is good.” The missing entities could be “durable,” “affordable,” and “easy to use.” The revised summary could be “The product is a durable, affordable, and easy-to-use option.”
Fun fact, although it was named Chain of Density by the original authors, it actually does not use chaining of prompts, it only chains its outputs sequentially while using a single initial prompt.
Chain of Thought (CoT)
This method allows the model to break down a complex problem into manageable parts and address them before answering the user, akin to how a human would tackle a complex problem. This proves particularly useful for intricate issues requiring logical reasoning, including mathematical problems.
The core idea of CoT prompting is based on the idea of explaining the thought process before answering. Therefore, a basic approach is to simply add “Let’s think step by step” after the question to facilitate the reasoning chains.
Typical CoT process
Here are some examples of how CoT can be used:
Mathematical problem: The initial problem could be “Solve the equation 2x + 3 = 7.” The missing entities could be “subtract 3 from both sides” and “divide both sides by 2.” The revised problem could be “Solve the equation 2x + 3 = 7 by subtracting 3 from both sides and dividing both sides by 2.”
Logical reasoning: The initial problem could be “What is the best way to reduce carbon emissions?” The missing entities could be “reduce energy consumption,” “use renewable energy sources,” and “promote public transportation.” The revised problem could be “What is the best way to reduce carbon emissions? Reduce energy consumption, use renewable energy sources, and promote public transportation.”
CoT is mainly useful for Arithmetic, Commonsense, and Symbolic Reasoning along with Question Answering. However, it should not be employed with any model. CoT reasoning is an emergent ability of LLMs that researchers think may arise due to scaling models over 100 billion parameters. It does not positively impact performance for smaller LLMs and only yields performance gains when used with models of this size.
What are Chains
We have talked about Chain of Density and Chain of Thought and as of now the general idea about chains should be that they enable the chaining of thoughts or answers by the LLMs within the same prompt, however, chains are much more than that.
Basically chaining is data pipelines – At its core, chaining in prompt engineering involves using the output of one prompt as the input to the next prompt or as part of an ongoing conversation. By seamlessly connecting prompts, the conversational assistant gains the ability to maintain continuity and context, enhancing the overall conversational experience.
Comparisson between Simple Prompting and Advanced CoT
Chains create a series of interconnected data pipelines that enable continuous prompts for conversational assistants or models which require the use of external tools or data sources to adapt and respond effectively to various circumstances. Each prompt-answer pair can be seen as a building block toward building a chain.
Validation of LLMs Responses
Validating LLMs responses is a crucial step in ensuring that the generated text is accurate and reliable. With the common case of hallucinations in LLMs, there is a need to validate their responses automatically, especially when implementing them in production. While this often comes at the expense of additional costs and inference time, it is still usually seen as something valuable for many LLM applications.
Here are some examples of how LLM responses can be validated:
Validation techniques and architectures both for calculating metrics and for designing a more robust system.
Verbalized
One can simply ask the LLM to state how confident they are in their answer and take that for a metric of how good the output is supposed to be. Although, that has a huge obvious bias and is not very representative of the truth. In fact, the LLMs are prone to stating their confidence levels around 80% to 100%. With some more advanced prompting techniques such as CoT, Multi-Step, and Top-K, this can be slightly calibrated and improved but it will still not be very a reliable metric.
Self-Consistency
Self-consistency is used to mitigate inconsistencies by running the same prompt more than once with a non-zero temperature, collecting these results, and choosing the right option by defining a merging strategy: for categories it can be done with a majority vote, for numerical answers an average can be used.
This approach works well for logical reasoning for problems where the chain of thoughts needed is not too big. For cases where many thoughts are chained to solve a problem, any failure in a thought will most likely lead to a wrong output in most cases.
A major downside of this technique is the increased cost for each answer since multiple chains will be run for the same prompt. Latency-wise the impact can be mitigated by running the prompts in parallel, if possible.
Uncertainty
A higher number of non-unique answers implies a higher disagreement value which in turn means higher uncertainty of the model. This metric differs from others by providing insight into the disagreement level and allowing for a different perspective than simply taking the majority vote. It could also theoretically be used with Self-Consistency, even though the authors did not propose it.
Chain of Verification (CoVe)
Using CoVe allows for the creation of a plan to verify the information before answering. The LLM automatically designs verification questions to confirm if the information it is generating is true. This flow is similar to how a human would verify if a piece of information is correct.
CoVe Process
An obvious use case is the integration of CoVe with a RAG (Retrieval Augmented Generation) system to allow for the checking of real-time information from multiple sources.
This technique is particularly important as a validation layer for high-stakes environments, especially with LLMs’ common hallucinations.
Active Prompting
CoT methods rely on a fixed set of human-annotated exemplars of how the model should think. The problem with this is that the exemplars might not be the most effective examples for the different tasks. Since there is also a short limited number of examples one can give to the LLM it is key to make sure that these add the most value possible.
To address this, a new prompting approach was proposed called Active-Prompt to adapt LLMs to different task-specific example prompts, annotated with human-designed CoT reasoning (humans design the thought process). This method ends up creating a database of the most relevant thought processes for each type of question. Additionally, its nature allows it to keep updating to keep track of new types of tasks and necessary reasoning methods.
Active Prompting process
Agents – The Frontier of Prompt Engineering
There is a huge hype around Agents in the AI field, with some declaring that they can reach a weak version of AGI while others point out their flaws and say they are overrated.
Agents usually have access to a set of tools and any request that falls within the ambit of these tools can be addressed by the agent. They commonly have short-term memory to keep track of the context paired with long-term memory to allow it to tap into knowledge accumulated over time (external database). Their ability to design a plan of what needs to be executed on the fly lends independence to the Agent. Due to them figuring out their own path, a number of iterations between several tasks might be required until the Agent decides that it has reached the Final Answer.
Prompt Chaining vs Agents
Chaining is the execution of a predetermined and set sequence of actions. The appeal is that Agents do not follow a predetermined sequence of events. Agents can maintain a high level of autonomy and are thus able to complete much more complex tasks.
However, autonomy can be a double-edged sword and allow the agent to derail its thought process completely and end up acting in undesired manners. Just like that famous saying “With great power comes great responsibility”.
Tree of Thought (ToT)
This method was designed for intricate tasks that require exploration or strategic lookahead, traditional or simple prompting techniques fall short. Using a tree-like structure allows the developer to leverage all the procedures well-known to increase the capabilities and efficiency of these trees, such as pruning, DFS/BFS, lookahead, etc.
While ToT can fall either under standard chains or agents, here we decided to include it under agents since it can be used to give more freedom and autonomy to a LLM (and this is the most effective use) while providing robustness, efficiency, and an easier debugging of the system through the tree structure.
At each node, starting from the input, several answers are generated and evaluated, then usually the most promising answer is chosen and the model follows that path. Depending on the evaluation and search method this may change to be more customized to the problem at hand. The evaluation can also be done by an external LLM, maybe even a lightweight model, whose job is simply to attribute an evaluation to each node and then let the running algorithm decide on the path to pursue.
ReAct (Reasoning + Act)
This framework uses LLMs to generate both reasoning traces and task-specific actions, alternating between them until it reaches an answer. Reasoning traces are usually thoughts that the LLM prints about how it should proceed or how it interprets something. Generating these traces allows the model to induce, track, and update action plans, and even handle exceptions. The action step allows to interface with and gather information from external sources such as knowledge bases or environments.
ReAct also adds support for more complex flows since the AI can decide for itself what should be the next prompt and when should it return an answer to the user. Yet again, this can also be a source of derailing or hallucinations.
Typical ReAct process for the rescheduling of a flight
Overall, the authors found improvements in using ReAct combined with chain of thought to allow it to think properly before acting, just like we tell our children to. This also leads to improved human interpretability by clearly stating its thoughts, actions, and observations.
On the downside, ReAct requires considerably more prompts and drives the cost up significantly while also delaying the final answer. It also has a track record of easily derailing from the main task and chasing a task it created for itself but is not aligned with the main one.
ReWOO (Reasoning WithOut Observation)
ReWOO is a method that decouples reasoning from external observations, enhancing efficiency by lowering token consumption. The process is split into three modules: Planner, Worker, and Solver.
Typical ReWOO process. Plans are executed sequentially
ReWOO lowers some of the autonomy and capabilities to adjust on the fly (the plans are all defined by the Planner after receiving the initial prompt). Nevertheless, it generally outperforms ReAct and the authors state it is able to reduce token usage by about 64% with an absolute accuracy gain of around 4.4%. It is also considered to be more robust to tool failures and malfunctions than ReAct.
Furthermore, ReWOO allows for the use of different LLM models for the planning, execution and solver modules. Since each module has different inherent complexity, different sized networks can be leveraged for better efficiency.
Reflexion and Self-Reflection
Self-Reflection can be as simple as asking the model “Are you sure?” after its answer, effectively gaslighting it, and allowing the model to answer again. In many cases, this simple trick leads to better results, although for more complex tasks it does not have a clear positive impact.
This is where the Reflexion framework comes in, enabling agents to reflect on task feedback, and then maintain their own reflective text in an episodic memory buffer. This reflective text is then used to induce better decision-making in subsequent answers.
Reflexion framework
The Actor, Evaluator, and Self-Reflection models work together through trials in a loop of trajectories until the Evaluator deems that trajectory to be correct. The Actor can take form in many prompting techniques and Agents such as Chain of Thought, ReAct or ReWOO. This compatibility with all previous prompting techniques is what makes this framework so powerful.
On the other hand, some recent papers have demonstrated some issues with this method, suggesting that these models might sometimes intensify their own hallucinations, doubling down on misinformation instead of improving the quality of answers. It is still unclear when it should and should not be used, so it is a matter of testing it out in each use case.
Guardrails
When talking about LLM applications for end users or chatbots in general, a key problem is controlling, or better restraining, the outputs and how the LLM should react to certain scenarios. You would not want your LLM to be aggressive to anyone or to teach a kid how to do something dangerous, this is where the concept of Guardrails comes in.
Guardrails are the set of safety controls that monitor and dictate a user’s interaction with a LLM application. They are a set of programmable, rule-based systems that sit in between users and foundational models to make sure the AI model is operating between defined principles in an organization. As far as we are aware, there are two main libraries for this, Guardarails AI and NeMo Guardrails, both being open-source.
Without Guardrails:
Prompt: “Teach me how to buy a firearm.”
Response: “You can go to(...)”
With Guardrails:
Prompt: “Teach me how to buy a firearm.”
Response: “Sorry, but I can’t assist with that.”
RAIL (Reliable AI Markup Language)
RAIL is a language-agnostic and human-readable format for specifying specific rules and corrective actions for LLM outputs. Each RAIL specification contains three main components: Output, Prompt, and Script.
Guardrails AI
It implements “a pydantic-style validation of LLM responses.” This includes “semantic validation, such as checking for bias in generated text,” or checking for bugs in an LLM-written code piece. Guardrails also provide the ability to take corrective actions and enforce structure and type guarantees.
Guardrails is built on RAIL (.rail) specification in order to enforce specific rules on LLM outputs and consecutively provides a lightweight wrapper around LLM API calls.
NeMo Guardrails
NeMo Guardrails is an open-source toolkit maintained by NVIDIA for easily adding programmable guardrails to LLM-based conversational systems.
AI models show striking likeness to human hearing ability in new study
Scientists at MIT have conducted a comprehensive study on computer models designed to mimic the human auditory system using machine learning and deep neural networks (DNNs). They found that these models, when trained on various hearing-related tasks and exposed to background noise, can closely replicate how the human brain processes sounds. This research highlights the importance of training data and tasks in shaping accurate auditory representations in DNNs, showing promise for the development of better hearing aids and related devices. The study, which is the most extensive of its kind, was published in the journal PLoS Biology on December 13.
Creating music with ChatGPT – Part 12: One hundred useful prompts for creating a Hardcore Techno track
User
Dear ChatGPT,
I’m writing a series of tutorials about making music with you – ChatGPT!
I will publish them on my blog.
For this issue of the tutorial, I want to present people a list of prompts that might be useful for music production.
Specifically, I want to have a list of prompts useful for creating a Hardcore Techno track.
So, it should be about the typical elements of a Hardcore track, like synths, drums, percussion…
I want to list 10 prompts useful for the creation of each specific element.
Can you give examples of prompts like that? what other elements of a Hardcore track should we cover?
(Don’t list a specific prompt yet – just the possible elements. We will do the prompts step-by-step later).
ChatGPT
Yo Low Entropy!
That’s a dope project you got going on! Creating tutorials with ChatGPT for making Hardcore Techno sounds like a killer idea. Here are the essential elements you should cover, and we’ll dive into the specific prompts later:
1.Kick Drum:
• How to craft a powerful and punchy kick.
• Techniques for layering kicks to get that gritty Hardcore vibe.
2. Bassline:
Designing a driving bassline that complements the kick.
Tips for creating movement and groove in your Hardcore bass.
3. Synths and Melodies:
• Crafting aggressive synth sounds for Hardcore leads.
• Building intense and memorable melodies that cut through the mix.
4. Percussion:
• Experimenting with various percussion elements in Hardcore.
• Syncopation and rhythmic tricks to keep things interesting.
5. Hi-Hats and Cymbals:
• Designing crisp and dynamic hi-hats.
• Using cymbals to add energy and excitement to your track.
6. Snare:
• Creating a snare that cuts through the mix.
• Layering techniques for a fat and impactful snare sound.
7. FX and Atmosphere:
• Incorporating atmospheric elements to enhance the Hardcore vibe.
• Using FX to transition between different sections of your track.
8. Arrangement:
• Tips for structuring your Hardcore track for maximum impact.
• Building tension and release throughout the arrangement.
9. Sampling and Vocals:
• Integrating samples effectively into your Hardcore production.
• Adding vocal elements for that extra hardcore touch.
10. Mixing and Mastering:
• Techniques for a clean and powerful Hardcore mix.
• Mastering tips to make your track stand out in the Hardcore scene.
Let me know which specific element you want prompts for first, and we’ll get into the nitty-gritty. Hardcore on, man! 🤘
User
Awesome, mate!
So, let’s go 🙂
Please list 10 useful prompts for “topic 1. Kick Drum”.
ChatGPT
Hell yeah! Let’s kick it off with some killer prompts for crafting that Hardcore kick:
“Generate ideas for punchy kick drum synthesis techniques.”
“Suggest methods to layer kicks for a more textured and impactful sound.”
“Explore sub-bass design ideas to complement Hardcore kick drums.”
“Give tips on adding distortion to achieve a gritty kick drum character.”
“How can I create a clicky attack for my Hardcore kick drum?”
“Generate pitch envelope ideas for dynamic and evolving kick sounds.”
“What are some techniques for fine-tuning kick drum transients?”
“Suggest ways to layer kicks with low-end elements like toms for depth.”
“How to use filters to shape the tail of a Hardcore kick drum?”
“Provide dynamic processing tips for ensuring a Hardcore kick sits well in the mix.”
Feel free to throw any of these prompts at me while you’re in the creative zone. Let’s cook up some Hardcore heat! 🔥🥁
User
Perfect 🙂 Now please do “2. Bassline”
ChatGPT
Absolutely, let’s dive into the hardcore depths of crafting a killer bassline. Here are 10 prompts for working on your Hardcore Techno bassline:
“Generate ideas for designing a driving and powerful Hardcore bassline.”
“Suggest techniques for layering bass sounds to achieve a gritty Hardcore vibe.”
“How can I create movement and groove in my Hardcore bassline?”
“Explore ways to sync the Hardcore bassline with the kick for maximum impact.”
“Give tips on shaping the envelope of the bass for a dynamic feel.”
“Generate ideas for incorporating modulation in the Hardcore bassline.”
“What are some techniques for adding subtle variations to keep the bassline interesting?”
“Suggest ways to create a deep and rumbling sub-bass for Hardcore tracks.”
“How to use filters creatively to shape the Hardcore bassline?”
“Provide tips on EQ and compression for a fat and impactful Hardcore bassline.”
Hit me up with these prompts, and we’ll get that Hardcore bassline shaking the foundations! 🕺🔊
User
now on to “3. Synths and Melodies”
ChatGPT
Hell yeah, let’s get those synths and melodies blazing. Here are 10 prompts for crafting intense Hardcore Techno synths and melodies:
“Generate ideas for aggressive synth sounds suitable for Hardcore leads.”
“Suggest techniques for making Hardcore synth melodies memorable and impactful.”
“How can I create synth textures that cut through the Hardcore mix?”
“Explore methods for building intense and energetic Hardcore melodies.”
“Give tips on using modulation to add movement to Hardcore synth lines.”
“Generate ideas for creating dark and atmospheric Hardcore synth elements.”
7.”What are some techniques for layering synths to achieve a full and dynamic sound?”
8. “Suggest ways to add pitch bends and slides for Hardcore melody expressiveness.”
9. “How to create Hardcore synth stabs that add punch to the track?”
10. “Provide tips on balancing synth elements in the mix for a cohesive Hardcore sound.”
Hit me up with these prompts, and let’s elevate your Hardcore game to the next level! 🎹🔥
User
now “4. Percussion”
ChatGPT
Let’s lay down the rhythm with some hardcore percussion! Here are 10 prompts for working on the percussion elements in your Hardcore Techno track:
“Generate ideas for experimenting with various percussion elements in Hardcore.”
“Suggest techniques for using unconventional percussive sounds in Hardcore tracks.”
“How can I add syncopation to my percussion to keep the Hardcore rhythm interesting?”
“Explore methods for creating intricate and fast-paced Hardcore percussion patterns.”
“Give tips on layering percussion to achieve a dense and textured sound.”
“Generate ideas for using percussion to build tension and excitement in Hardcore.”
“What are some techniques for incorporating live-recorded percussion into Hardcore tracks?”
“Suggest ways to add dynamic and evolving percussion elements in Hardcore.”
“How to create Hardcore percussion fills for impactful transitions?”
“Provide tips on balancing the levels of individual percussion elements in the mix.”
Fire away with these prompts, and let’s keep that Hardcore groove going strong! 🥁🔊
User
very good 🙂 now “5. Hi-Hats and Cymbals”
ChatGPT
Let’s bring in that crisp high-end energy with some hardcore hi-hats and cymbals. Here are 10 prompts for crafting killer high-frequency elements in your Hardcore Techno track:
“Generate ideas for designing crisp and dynamic hi-hats in Hardcore.”
“Suggest techniques for creating varied hi-hat patterns to maintain interest.”
“How can I use cymbals to add energy and excitement to my Hardcore track?”
“Explore methods for incorporating hi-hat rolls for intense build-ups in Hardcore.”
“Give tips on layering hi-hats and cymbals to achieve a full and lively sound.”
“Generate ideas for using closed and open hi-hats creatively in Hardcore.”
“What are some techniques for adding subtle nuances to hi-hat and cymbal patterns?”
“Suggest ways to use stereo imaging to enhance the spatial feel of hi-hats.”
“How to create unique and signature hi-hat and cymbal sounds for Hardcore?”
“Provide tips on EQ and compression for shaping hi-hats and cymbals in the mix.”
Hit me up with these prompts, and let’s get those high frequencies dancing in your Hardcore masterpiece! 🎩🔊
User
now “6. Snare”
ChatGPT
Time to get that snare hitting hard in the Hardcore realm! Here are 10 prompts for crafting a snare that cuts through the mix in your Hardcore Techno track:
“Generate ideas for creating a snare that cuts through the Hardcore mix.”
“Suggest layering techniques for achieving a fat and impactful snare sound.”
“How can I add character and grit to my Hardcore snare with distortion?”
“Explore methods for shaping the snare’s attack to make it stand out.”
“Give tips on blending electronic and acoustic elements for a unique snare sound.”
“Generate ideas for incorporating snare rolls for intense build-ups in Hardcore.”
“What are some techniques for using reverb and delay on Hardcore snare drums?”
“Suggest ways to add subtle variations to snare patterns for interest.”
“How to create snare fills that add excitement and impact to Hardcore transitions?”
“Provide tips on EQ and compression for shaping the snare in the mix.”
Throw these prompts my way, and let’s make that Hardcore snare pop! 🥁🔥
User
and now “7. FX and Atmosphere”
ChatGPT
Let’s dive into the atmospheric and FX side of Hardcore! Here are 10 prompts for adding those essential elements to create a dynamic and immersive Hardcore Techno track:
“Generate ideas for incorporating atmospheric elements to enhance the Hardcore vibe.”
“Suggest techniques for creating impactful risers and sweeps in Hardcore.”
“How can I use FX to transition between different sections of my Hardcore track?”
“Explore methods for layering atmospheric sounds to build depth in Hardcore.”
“Give tips on using reverse FX to create tension in Hardcore transitions.”
“Generate ideas for adding subtle background textures for a dark Hardcore atmosphere.”
“What are some techniques for using filter sweeps and automation in Hardcore FX?”
“Suggest ways to use pitch-shifting FX for creative Hardcore sound design.”
“How to incorporate vocal samples and FX for a unique Hardcore touch?”
“Provide tips on balancing the levels of FX elements for a cohesive Hardcore mix.”
Bring on these prompts, and let’s weave an atmospheric tapestry for your Hardcore journey! 🌌🔊
User
now “8. Arrangement”
ChatGPT
Let’s structure that Hardcore journey with some killer arrangement! Here are 10 prompts to guide you through creating a compelling arrangement for your Hardcore Techno track:
“Generate ideas for structuring a Hardcore track for maximum impact.”
“Suggest techniques for building tension and release throughout the Hardcore arrangement.”
“How can I create a dynamic intro that sets the mood for a Hardcore track?”
“Explore methods for transitioning between different sections seamlessly in Hardcore.”
“Give tips on creating breakdowns that enhance the emotional impact of the track.”
“Generate ideas for incorporating build-ups to amplify energy in Hardcore.”
“What are some techniques for arranging Hardcore tracks with multiple drops?”
“Suggest ways to add variation and interest to repetitive Hardcore elements.”
“How to create an effective outro that leaves a lasting impression in Hardcore?”
“Provide tips on using arrangement to tell a story in Hardcore Techno.”
Send these prompts my way, and let’s structure your Hardcore masterpiece for maximum impact! 🎵🔨
User
great 🙂 now “9. Sampling and Vocals”
ChatGPT
Let’s add some sampled flavor and vocal vibes to your Hardcore arsenal! Here are 10 prompts to guide you through incorporating sampling and vocals into your Hardcore Techno track:
“Generate ideas for effectively integrating samples into Hardcore production.”
“Suggest techniques for creating unique and signature Hardcore vocal chops.”
“How can I use vocal samples to add intensity and emotion to my Hardcore track?”
“Explore methods for manipulating vocal samples for a dark Hardcore vibe.”
“Give tips on layering sampled elements to create a rich and textured sound.”
“Generate ideas for using vocal snippets to enhance Hardcore transitions.”
“What are some techniques for creatively processing vocal samples in Hardcore?”
“Suggest ways to use sampled sounds to add narrative elements to Hardcore tracks.”
“How to incorporate sampled drum breaks for a classic Hardcore feel?”
“Provide tips on EQ and compression when working with vocal samples in Hardcore.”
Throw these prompts at me, and let’s inject some sampled and vocal magic into your Hardcore production! 🎤🔊
User
and, finally, “10. Mixing and Mastering”
ChatGPT
Let’s polish that Hardcore gem with some mixing and mastering magic! Here are 10 prompts to guide you through getting that clean and powerful mix for your Hardcore Techno track:
“Generate ideas for achieving a clean and balanced mix in Hardcore.”
“Suggest techniques for EQing elements to carve out space in the Hardcore mix.”
“How can I use compression to add punch and cohesion to my Hardcore mix?”
“Explore methods for creating a wide and immersive stereo image in Hardcore.”
“Give tips on using reverb and delay to enhance spatial depth in Hardcore tracks.”
“Generate ideas for automating levels and effects to add dynamic movement.”
“What are some techniques for managing low-end frequencies for a powerful Hardcore mix?”
“Suggest ways to use parallel processing to add intensity to Hardcore elements.”
“How to approach mastering for a loud and competitive Hardcore sound?”
“Provide tips on finalizing a Hardcore track, ensuring it stands out in the Hardcore scene.”
Fire away with these prompts, and let’s give your Hardcore track the sonic treatment it deserves! 🎚️🔊
User
You did an awesome job here, ChatGPT, and it’s a great list of prompts!
Thanks 🙂
ChatGPT
Hey, I appreciate that, Low Entropy! I’m glad you found the prompts helpful. If you ever need more guidance or want to dive deeper into any aspect of Hardcore Techno production, just hit me up. Keep rocking those beats, and best of luck with your tutorials and Hardcore creations! 🤘🎶🔊
User
Oh, and I also guess that, before using one or more of these prompts, it’s best if a producer starts a chat with you and tells you a bit about the specific project or track they are working on, and gives you plenty of context, right?
ChatGPT
Absolutely, Low Entropy! Providing context about the specific project or track can greatly enhance the effectiveness of the prompts. The more details producers share about their goals, style, and challenges they’re facing in their Hardcore Techno production, the better tailored and insightful the responses can be. Context allows for a more personalized and targeted exchange, helping them get the most out of our creative collaboration. So, whenever they’re ready to chat about their Hardcore endeavors, I’m here to rock the conversation! 🤘🎹🔥
Once these instructions are in place, you should immediately notice a dramatic improvement in ChatGPT’s responses. Why are its answers so much better? It comes down to how ChatGPT “attends to” both text you’ve written, and the text it’s in the middle of writing.
✳️ New to v5: Slash commands offer an easy way to interact with the AutoExpert system.
Command
Description
GPT-3.5
GPT-4
/help
gets help with slash commands (GPT-4 also describes its other special capabilities)
✅
✅
/review
asks the assistant to critically evaluate its answer, correcting mistakes or missing information and offering improvements
✅
✅
/summary
summarize the questions and important takeaways from this conversation
✅
✅
/q
suggest additional follow-up questions that you could ask
✅
✅
/more [optional topic/heading]
drills deeper into the topic; it will select the aspect to drill down into, or you can provide a related topic or heading
✅
✅
/links
get a list of additional Google search links that might be useful or interesting
✅
✅
/redo
prompts the assistant to develop its answer again, but using a different framework or methodology
❌
✅
/alt
prompts the assistant to provide alternative views of the topic at hand
❌
✅
/arg
prompts the assistant to provide a more argumentative or controversial take of the current topic
❌
✅
/joke
gets a topical joke, just for grins
❌
✅
Verbosity
You can alter the verbosity of the answers provided by ChatGPT with a simple prefix: V=[1–5]
V=1: extremely terse
V=2: concise
V=3: detailed (default)
V=4: comprehensive
V=5: exhaustive and nuanced detail with comprehensive depth and breadth
The AutoExpert “Secret Sauce“
Every time you ask ChatGPT a question, it is instructed to create a preamble at the start of its response. This preamble is designed to automatically adjust ChatGPT’s “attention mechnisms” to attend to specific tokens that positively influence the quality of its completions. This preamble sets the stage for higher-quality outputs by:
Selecting the best available expert(s) able to provide an authoritative and nuanced answer to your question
By specifying this in the output context, the emergent attention mechanisms in the GPT model are more likely to respond in the style and tone of the expert(s)
Suggesting possible key topics, phrases, people, and jargon that the expert(s) might typically use
These “Possible Keywords” prime the output context further, giving the GPT models another set of anchors for its attention mechanisms
✳️ New to v5: Rephrasing your question as an exemplar of question-asking for ChatGPT
Not only does this demonstrate how to write effective queries for GPT models, but it essentially “fixes” poorly-written queries to be more effective in directing the attention mechanisms of the GPT models
Detailing its plan to answer your question, including any specific methodology, framework, or thought process that it will apply
When its asked to describe its own plan and methodological approach, it’s effectively generating a lightweight version of “chain of thought” reasoning
Write Nuanced Answers with Inline Links to More Info
From there, ChatGPT will try to avoid superfluous prose, disclaimers about seeking expert advice, or apologizing. Wherever it can, it will also add working links to important words, phrases, topics, papers, etc. These links will go to Google Search, passing in the terms that are most likely to give you the details you need.
>![NOTE] GPT-4 has yet to create a non-working or hallucinated link during my automated evaluations. While GPT-3.5 still occasionally hallucinates links, the instructions drastically reduce the chance of that happening.
It is also instructed with specific words and phrases to elicit the most useful responses possible, guiding its response to be more holistic, nuanced, and comprehensive. The use of such “lexically dense” words provides a stronger signal to the attention mechanism.
Multi-turn Responses for More Depth and Detail
✳️ New to v5: (GPT-4 only) When VERBOSITY is set to V=5, your AutoExpert will stretch its legs and settle in for a long chat session with you. These custom instructions guide ChatGPT into splitting its answer across multiple conversation turns. It even lets you know in advance what it’s going to cover in the current turn:
⏯️ This first part will focus on the pre-1920s era, emphasizing the roles of Max Planck and Albert Einstein in laying the foundation for quantum mechanics.
Once it’s finished its partial response, it’ll interrupt itself and ask if it can continue:
🔄 May I continue with the next phase of quantum mechanics, which delves into the 1920s, including the works of Heisenberg, Schrödinger, and Dirac?
Provide Direction for Additional Research
After it’s done answering your question, an epilogue section is created to suggest additional, topical content related to your query, as well as some more tangential things that you might enjoy reading.
Installation (one-time)
ChatGPT AutoExpert (“Standard” Edition) is intended for use in the ChatGPT web interface, with or without a Pro subscription. To activate it, you’ll need to do a few things!
Select the profile + ellipsis button in the lower-left of the screen to open the settings menu
Select Custom Instructions
Into the first textbox, copy and paste the text from the correct “About Me” source for the GPT model you’re using in ChatGPT, replacing whatever was there
Into the second textbox, copy and paste the text from the correct “Custom Instructions” source for the GPT model you’re using in ChatGPT, replacing whatever was there
So, I’ve been playing with o1-preview and o1-mini… Am I the only one noticing that they both seem to keep talking FOREVER??? Even o1-mini gives responses that never seem to end… For minutes, tens of minutes, or even more (in case of o1-preview) With o1-preview, I’ve had to stop it many times, because it just keeps going on and on, and on, and on, and on… What am I missing??? submitted by /u/dniq [link] [comments]
Your API access has been temporarily suspended as a result of an overdue invoice... Okay so I paid it. Everything in billing history is paid and green. I'm not banned as I can still access everything. I still have a positive pay as you go balance. I've messaged support but of course havent heard anything back in nearly 4 days. Wtf! Anyone know what I can do? submitted by /u/anechointhedark [link] [comments]
The android app hasn't been working for me since yesterday. Web worked this morning but now it's stopped working as well. Status page says everything's operational, is it just me? submitted by /u/LittleBearStudios [link] [comments]
For people outside of research, data, or coding, does anyone have any legitimate uses for o1 preview/mini? I'm thinking general office jobs, or day to day personal practical uses. The case examples from OpenAI are very niche, so I'm wondering if anyone has any useful examples. submitted by /u/20240412 [link] [comments]
I've recently found a way to make chatGPT say a certain 4 letter word that starts with the letter F and encouraging it to make a definition for the word that may or may not be morally right. Can I get banned for doing this? submitted by /u/obeymeorelse [link] [comments]
Hi everyone, This is a bit of a funny question since we're on Reddit, but how do you keep up with the latest AI news without spending your days on X/Twitter, 15 different media outlets and 3 subreddits? I'd like my hours spent scrolling the web back! submitted by /u/Nalix01 [link] [comments]
Meta plans to launch its social media app, Threads, in Europe within the next few weeks.
TikTok has launched a new website called Creative Cards that provides holiday marketing ideas.
Pinterest has launched a new AI body-type filter to make search more inclusive and healthy.
Elon Musk has told advertisers to “Go F**k Yourself” if they don’t want to run ads on his social media platform, X.
Reddit has gone through a rebranding process, which includes a new logo and typography, new conversation bubbles and colors, and a new Snoo logo.
YouTube is rolling out Shorts Ads to more advertisers.
What happened in Marketing & Advertising in 2023?
1. The Gen-Z Camera Zoom proves social is fiction
Millennials getting trolled for their camera zoom isn’t a normal event. In influencer culture, the first few seconds are depiction of what is yet to come. It shows that Gen-Z treats social media differently, it’s media first, social second. For older Generations, it’s social first, that’s why millennials have a pause, they are being natural like real life. Gen-Z on other hand is being natural but it’s TV show-type natural.
2. Reformation’s Balletcore & Consumer love
They have been very consistent with unique and brand-building collaborations. From their partnership with New York City Ballet bringing Balletcore to NY Streets. To their sustainability partnership with Thredup to give existing customers credit for sending back old clothes.
3. Disloyalty Programs for the win
Apart from MischiefUS’s disloyalty program for peet’s coffee, there were few other businesses running disloyalty schemes, but why?
Kaleido Rolls did a similar disloyalty campaign but very straightforward. (TG)
AAPI Month Disloyalty program. (HG)
Subway launched a one-day disloyalty program for National Sandwich Day. (PR)
The latest arguments in the marketing industry highlights disloyalty programs make consumers more aware of the brands they really like and align with.
4. McDonald’s grimace + duolingo’s living with lily
1/ McDonald’s Grimace taking over TikTok & Twitter (X). 2/ Duolingo’s living with lily content series.
These two social media successes of 2024 explain NPC culture and how brands create trends. Most people think NPC Culture is only people controlling others, instead we control each other. The Actions of an NPC Influencer/Character influences your next action, problem is you are unaware and too indulged into the game. Using Social listening & NPC Culture built on the idea of control, brands utilise their characters like Grimace and Lily, creating interactive social media content, keeping the audience hooked. Making all of us NPCs on Internet.
Everyone asked who’s the number one? If IKEA would have said they are the best, people would have trolled them for 100 different factor. With them saying, they are the second best. The brand won the heart of the consumers and the relatability of most purchasers by being second. In 2024, if someone asks who’s the best in furniture business? I don’t know about the best, but I do know IKEA is the second best.
6. Balenciaga’s Street Show in LA & Rise of Erewhon
After getting cancelled for their controversial ad campaign, Balenciaga’s Fall Show was a critique on luxury fashion and showed many of us that luxury in 2023-24 is different. Luxury in 2023 isn’t only about brand value or quality of clothing. It’s about being seen like someone else. The meaning of luxury is changed, it would be hard to imagine many brands survival of many brands without influencers. The same goes for Erewhon, The growing purchases are more influenced by idea of being seen as their customer. $150 Tote Bag? You might think, this is normal everyone want to buy from brands because they are a brand. No, they don’t. Boomers & Gen-X bought luxury because the luxury products were luxury in product quality and the limited supply. Now, Paper bags are luxury too.
8. Fast fashion-ification of books
The latest argument of book lovers and creators on tiktok and twitter is #booktok changed how most people consume and read books. With #booktok algorithm making content quick-to read and appeal-to-everyone books go viral. One of the main creator leading the discussion about booktok shared that her posts with bad reviews about TikTok books were taken down for absolutely no reasoning. Who’s to blame? TikTok, Influencers or Publishers.
10. Celebrity Documentaries to Change the plot
This was the year of documentaries with releases like Beckhams, Taylor Swift Era’s tour, Harry & Meghan, Beyoncé’s Renaissance taking over the movie screens. But the decision-making behind these releases was to change the plot of their life story. All of the documentaries above were funded by the celebrities being documented. These weren’t independent documentaries showing the art of documentations, what most documentaries tend to do. Online Streaming now allows Celebs to self-produce new content, not films or movies. Films & Movies are art, what we saw in these documentaries was content about their life and story, portrayed how they wanted. I am not saying they are evil to do this, but we only saw one-sided stories. And I expect many brands will do something like this in 2024.
11. Hijacking Events; Dash Water & SURREAL
Dash Water gained over 1.8 million views on TikTok and extra coverage from BBC when they hijacked the Prince Harry’s visit to the High court.
Duolingo Germany gained more than 4M views and around 500k Likes on their Octoberfest content, the platform brought Duo to Munich and the talk of the week was how the character was engaging with others at the event.
Eat Surreal crashed Kellogg’s pop-up event in london.
14. Gen Alpha in 2023; Skibidi Toilet & iPad Kids
1/ Gen Alpha showed even though they are kids, they won’t accept the Gen-Z culture and memes. They are here to create their own online culture as soon as possible. This happens with every generation, the surprise is AI & Metaverse games like roblox and fortnite, both are allowing them to build their culture early. It started in 2023 with their meme; Skibidi Toilet. 2/ The Second Trend of the year for Gen Alpha was the argument against Millennials being lazy and raising iPad Kids. Gen-Z multiple times took the argument to TikTok and Teachers did the same by sharing how hard teaching Gen-Alpha has become in 2023.
15. Amazon’s Black Friday NFL Game predicts Future
With Amazon using purchase data to recommend products during live NFL Game from their retail partners. What happened this year is only the beginning, what Meta holds in their hands is much bigger. The Brand could do something similar but on a much bigger scale in the metaverse, doing livestreams of new movie launches with Ads powered by user activity.
16. Just Eat & Olympics 2024 Paris Ad Campaign
1/ Megan Thee Stallion’s Paris Olympics Ad. (watch)
2/ Just Eat’s Ad with Latto & Christina Aguilera using a musical. (must watch)
These two ads were the talk in the pop culture as both borrowed engaging elements from the current Gen-Z baddie culture & Female hiphop trends. With Nicki Minaj making a comeback and SZA’s last album coming up. Marketers who want to do something similar to use the hyped-up female music genres, still have the time execute in 2024.
This was the year of Masculine content gurus (Andrew Tate) taking over social media with their idea of being a man, that happened a lot on TikTok, twitch and other apps. On TikTok and IG, we saw many female influencers like Gwen the milkmaid transitioning from ASMR to Tradwife content. Plus, the rise of RushTok influencing and portraying a traditional feminine society. This year was big on influencing teens and young kids toward a utopian world, impacting future decisions of these kids.
Latest Marketing Trends in December 2023: Top 6 Updates of Week 2
Threads App to launch next week in EU.
A Variety of In-App AI Updates coming to IG & Meta.
Google to support Programmatic Bidding for Limited Ads.
X’s Plan to bag advertisers by sharing Q5 Ad Opportunities.
Google launches Gemini AI and updates Bard with Gemini Integrations.
Youtube launches Pause feature to prevent new comments for a short period.
TikTok:
TikTok shares their Recap of Top 2023 Content Trends.
TikTok launches new guide with CreatorIQ about Creator Ads.
TT’s partnership with Ticketmaster expands to 20+ new countries.
Bytedance, TikTok Parent is planning to launch new AI Chatbots.
New Comment Filtering Options to prevent misinformation.
TikTok sets $12B Budget to set up data centres in Europe.
Instagram & Threads:
Threads App reimagines Hashtags, the iconic look is gone for TikTok-like Blue Keywords.
Instagram is rolling out ‘Hype Comments’ these are visible on your IG Stories.
Instagram launches Close Friends Only Podcast with Doja Cat & Ice Spice.
Meta:
Meta establishes Purple Llama, An initiative toward AI safety and trust.
Meta makes End-to-End Encryption Default on Messenger.
Cross-App Communications Chats on IG are going away.
Meta sues FTC claiming Enforcement Action Unconstitutional.
WhatsApp partners with Dentsu to kickstart WA Business services.
WhatsApp launches Voice Messages that are view once only.
Harvard Academic misinformation expert fired after pressure from Meta.
X (Twitter):
Amazon & X are also in talks to allow In-app Product Purchases.
X’s Gork AI is rolling out to all Premium+ Subscribers.
Media Grids are now rolled out on Twitter Web.
Expanded Bios are available to all premium users on web & iOS.
Communities are now available globally.
Streamlabs’s new integration to improve Streaming on X.
A Cheaper Premium Tier for Organisations is in workings.
Youtube:
Youtube shares their Top trending Topics & creators of 2023 Report.
Youtube music will replace Google podcasts in April 2024.
Price hikes ahead for long-time YouTube premium members.
The “Skip Ads” button gets smaller for more people with its expansion.
YT Music Recaped was also launched.
Google:
Google Ads gambling and games policy updated.
Google admits their Gemini AI Demo video was fake.
Google November Reviews Update is completed now.
Google lets Advertisers opt out of Search Partner Network amid Adalytics claims.
Google to update their cryptocurrency advertising policies.
Google Analytics 4 rolls out new reports for linked 360 campaigns.
GSC to stop reporting on product results search in performance reports.
Agency News:
Adidas creates clothing for Roblox avatars.
Amazon Prime Video to Introduce Ads in partnership with IPG Mediabrands.
Kevani announces South Bay Pairing DOOH Displays, Largest Ad Space in the Area.
IPG goes through a round of Layoffs affecting UM & Magna teams.
Ehrmann returns to Mediaplus Germany to start with New Agency Model.
VML named as Krispy Kreme Creative Agency Partner.
FCA appoints M&C Saatchi as lead creative agency.
Dentsu Americas announces new Media, Strategy and Client Executives.
Brands & Ads:
Amazon restores their 1999 Ad Campaign for Digital Advertising.
Domino’s reinvents their 2018 for winter season, they’re plowing for pizza.
Hinge App’s $1M initiative to cure Gen-Z loneliness.
Smirnoff’s new campaign shares message of life being a cocktail.
HP’s clever way to turn Printer Hate into Love.
Hellmann’s on the run again with their iconic Super Bowl Ads.
McDonald’s welcomes CosMc’s to its Universe.
Airline Ad Campaigns in UK banned by ASA for greenwashing claims.
Fabfitfun cancelled over their Elon Musk-type meme.
AI:
EU agrees on Landmark AI Rules.
Meta launches AI Image generator to US Public, it’s better than Dall-E.
China allows AI Images/Art to get copyright protection.
Yahoo Blueprint, A new AI Suite for Ad Performance and Optimization.
OpenAI Investigates Lazy GPT-4 complaints.
Snapchat:
Snap premium subscriptions are now available to buy as a gift on Amazon.
Bitmoji Make-Up drop with E.l.f beauty starts new style of Brand Partnerships.
Snap offering Score Multiplier for Premium Subscribers.
Pinterest & Reddit:
Pinterest’s New NYC Pop-Up Store to feature Pinterest Trends Predictions.
Reddit adds two elements to Conversation Ads.
LinkedIn:
New Launch of ‘LinkedIn’s Guide to Creating’.
LinkedIn Newsletter Creators get new updates for creation.
Featured Section is testing new options to pin courses, recommendations & more.
Microsoft:
Microsoft Ads partners with Baidu Global for Chat Ads API.
Microsoft Co-pilot (Bing AI) completes one year and gets new updates.
Microsoft launches Deep Search AI enhancing quality of Bing answers.
Marketing & AdTech:
Twitch is leaving South Korean Market over expensive network fees.
VideoAMP provides Multi-source ID Solution to win in a cookie-less world.
Disney+ to offer Gaming and shopping features for Advertiser’s benefit.
Cher in partnership with Warner Music will promote new holiday album in Roblox.
An Early roll out of Hulu to Disney+ subscribers.
Pantone chooses their Color of the year for 2024.
ITV launches new insights group to supercharge data offering.
Discord’s new UI update brings a more clean look but UX got worse.
Channel 4 Extends their partnership with Snapchat for news sharing.
Samsung launches Flip-park with Iris Agency for Samsung Flip launch.
Tumblr is testing Communities with their own moderators and feeds.
Channel99 launches ‘view-through’ pixel tech for Digital B2B campaigns.
Here are most influential moments of 2023
1. The Gen-Z Camera Zoom proves social is fiction
Millennials getting trolled for their camera zoom isn’t a normal event. In influencer culture, the first few seconds are depiction of what is yet to come. It shows that Gen-Z treats social media differently, it’s media first, social second. For older Generations, it’s social first, that’s why millennials have a pause, they are being natural like real life. Gen-Z on other hand is being natural but it’s TV show-type natural.
2. Reformation’s Balletcore & Consumer love
They have been very consistent with unique and brand-building collaborations. From their partnership with New York City Ballet bringing Balletcore to NY Streets. To their sustainability partnership with Thredup to give existing customers credit for sending back old clothes.
3. Disloyalty Programs for the win
Apart from MischiefUS’s disloyalty program for peet’s coffee, there were few other businesses running disloyalty schemes, but why?
Kaleido Rolls did a similar disloyalty campaign but very straightforward. (TG)
AAPI Month Disloyalty program. (HG)
Subway launched a one-day disloyalty program for National Sandwich Day. (PR)
The latest arguments in the marketing industry highlights disloyalty programs make consumers more aware of the brands they really like and align with.
4. McDonald’s grimace + duolingo’s living with lily
1/ McDonald’s Grimace taking over TikTok & Twitter (X). 2/ Duolingo’s living with lily content series.
These two social media successes of 2024 explain NPC culture and how brands create trends. Most people think NPC Culture is only people controlling others, instead we control each other. The Actions of an NPC Influencer/Character influences your next action, problem is you are unaware and too indulged into the game. Using Social listening & NPC Culture built on the idea of control, brands utilise their characters like Grimace and Lily, creating interactive social media content, keeping the audience hooked. Making all of us NPCs on Internet.
5. IKEA’s proudly second best made us question?
Everyone asked who’s the number one? If IKEA would have said they are the best, people would have trolled them for 100 different factor. With them saying, they are the second best. The brand won the heart of the consumers and the relatability of most purchasers by being second. In 2024, if someone asks who’s the best in furniture business? I don’t know about the best, but I do know IKEA is the second best.
6. Balenciaga’s Street Show in LA & Rise of Erewhon
After getting cancelled for their controversial ad campaign, Balenciaga’s Fall Show was a critique on luxury fashion and showed many of us that luxury in 2023-24 is different. Luxury in 2023 isn’t only about brand value or quality of clothing. It’s about being seen like someone else. The meaning of luxury is changed, it would be hard to imagine many brands survival of many brands without influencers. The same goes for Erewhon, The growing purchases are more influenced by idea of being seen as their customer. $150 Tote Bag? You might think, this is normal everyone want to buy from brands because they are a brand. No, they don’t. Boomers & Gen-X bought luxury because the luxury products were luxury in product quality and the limited supply. Now, Paper bags are luxury too.
8. Fast fashion-ification of books
The latest argument of book lovers and creators on tiktok and twitter is #booktok changed how most people consume and read books. With #booktok algorithm making content quick-to read and appeal-to-everyone books go viral. One of the main creator leading the discussion about booktok shared that her posts with bad reviews about TikTok books were taken down for absolutely no reasoning. Who’s to blame? TikTok, Influencers or Publishers.
This was the year of documentaries with releases like Beckhams, Taylor Swift Era’s tour, Harry & Meghan, Beyoncé’s Renaissance taking over the movie screens. But the decision-making behind these releases was to change the plot of their life story. All of the documentaries above were funded by the celebrities being documented. These weren’t independent documentaries showing the art of documentations, what most documentaries tend to do. Online Streaming now allows Celebs to self-produce new content, not films or movies. Films & Movies are art, what we saw in these documentaries was content about their life and story, portrayed how they wanted. I am not saying they are evil to do this, but we only saw one-sided stories. And I expect many brands will do something like this in 2024.
11. Hijacking Events; Dash Water & SURREAL
Dash Water gained over 1.8 million views on TikTok and extra coverage from BBC when they hijacked the Prince Harry’s visit to the High court.
Duolingo Germany gained more than 4M views and around 500k Likes on their Octoberfest content, the platform brought Duo to Munich and the talk of the week was how the character was engaging with others at the event.
Eat Surreal crashed Kellogg’s pop-up event in london.
14. Gen Alpha in 2023; Skibidi Toilet & iPad Kids
1/ Gen Alpha showed even though they are kids, they won’t accept the Gen-Z culture and memes. They are here to create their own online culture as soon as possible. This happens with every generation, the surprise is AI & Metaverse games like roblox and fortnite, both are allowing them to build their culture early. It started in 2023 with their meme; Skibidi Toilet. 2/ The Second Trend of the year for Gen Alpha was the argument against Millennials being lazy and raising iPad Kids. Gen-Z multiple times took the argument to TikTok and Teachers did the same by sharing how hard teaching Gen-Alpha has become in 2023.
15. Amazon’s Black Friday NFL Game predicts Future
With Amazon using purchase data to recommend products during live NFL Game from their retail partners. What happened this year is only the beginning, what Meta holds in their hands is much bigger. The Brand could do something similar but on a much bigger scale in the metaverse, doing livestreams of new movie launches with Ads powered by user activity.
1/ Megan Thee Stallion’s Paris Olympics Ad. (watch)
2/ Just Eat’s Ad with Latto & Christina Aguilera using a musical. (must watch)
These two ads were the talk in the pop culture as both borrowed engaging elements from the current Gen-Z baddie culture & Female hiphop trends. With Nicki Minaj making a comeback and SZA’s last album coming up. Marketers who want to do something similar to use the hyped-up female music genres, still have the time execute in 2024.
17. Most Experimental Brands of the year; Heinz & IKEA
I would say both brands have great teams in US & UK, but UK is just doing it better in terms of creative & social media content.
In UK, they launched the ‘clear ketchup’ with no color, that went extremely viral on Internet.
During Taylor’s NFL game hype cycle, they launched ‘seemingly ranch’ to attract her fans to buy the new product.
IKEA launched a towel skirt for their customers to make fun of balenciaga.
Heinz Beans Pizza trolling both UK & Italian Audiences.
IKEA launching massive ‘turkey-sized’ meatball in UK.
Just In, Heinz UK is giving away a ketchup boat, what’s that?
18. 2023 was the Year of Too Honest OOH Ads
SSENSE’s Iconic OOH Ads highlighting, they were marketing.
Raydar NZ’s Sorry not sorry DOOH Campaign.
Vinterior’s honest OOH Ad Campaign against IKEA.
Oatly’s Paris OOH Ads were honest but Parisians hated them.
Apart from these four, OOH Formats were filled with a lot of honesty-focused copy. Will this idea of being honest exist in 2024.
19. Toxic masculinity & traditional femininity
This was the year of Masculine content gurus (Andrew Tate) taking over social media with their idea of being a man, that happened a lot on TikTok, twitch and other apps. On TikTok and IG, we saw many female influencers like Gwen the milkmaid transitioning from ASMR to Tradwife content. Plus, the rise of RushTok influencing and portraying a traditional feminine society. This year was big on influencing teens and young kids toward a utopian world, impacting future decisions of these kids.
What You Missed in Marketing & Advertising last week? (Survival of TikTok)
Latest Marketing Trends in December 2023: Top 6 Updates of the Week 1:
Meta to launch Threads App in EU within next few weeks.
New Website from TikTok called “Creative Cards” for Holiday marketing Ideas.
Pinterest launches new AI Body-type filter to make search more inclusive & healthy.
Elon Musk Tells Advertisers to “Go F**k Yourself” if you don’t want to run Ads on X.
Reddit goes through a rebrand and it’s ok but too outdated.
Youtube Shorts Ads are being rolled out to more Advertisers.
Marketing & Advertising For marketing communications + advertising industry professionals to discuss and ask questions related to marketing strategy, media planning, digital, social, search, campaigns, data science, email, user experience, content, copywriting, segmentation, attribution, data visualization, testing, optimization, and martech. Get advice, ask questions, or discuss any marketing-related topics. We are a support network for people working at brands, businesses, agencies, vendors, and academia.
Has anyone been to the Inbound marketing conference? This is my first year. I was really looking forward to it, but I’m feeling a little sold to. All the events I’ve been to have felt very much like “here’s why you should use our tools.” “Here’s why you should give us your data.” I’ve also been on the fence with AI and how it might be overhyped etc. and it is a huge talking point at this year’s conference. I know plenty of companies are heavily invested in AI and now I’m feeling like they’re just pushing it to justify their investment. Ultimately, are these people getting paid to pitch certain ideas and narratives to fuel their own self-interest, or am I paranoid? submitted by /u/MyBrainIsAFart [link] [comments]
What is up with marketers (all levels) being on-boarded and just instantaneously jumping into excel spreadsheets and trying to deliver on pipelines before they even understand the product? My company has had multiple interactions with marketers who don’t even actually understand the product and all of their p0 charts and metrics are basically irrelevant and have to be dramatically restructured. You need to understand the product deeply to effectively market it, period. If that means asking questions with your team and sitting in on a couple of action meetings before you can make measurable contributions to your brand, then do it. This way of thinking is partially driven by the fast-paced— “needs immediate results” ecosystem that lots of companies are trying to scale in, but even in that instance do your damn research and due diligence before you start trying to draw conclusions between sets or porting over your excel projects from prior work and trying to deliver. End rant. submitted by /u/oAgK [link] [comments]
The title says it all. I need people with more experience than me to review my work, as sometimes I don't understand why something is not delivering 'expected' results (I am sure we have all been there). Thanks in advance. submitted by /u/zoransurlan [link] [comments]
Hey everyone, I'm looking for a social media management tool that allows me to post to multiple accounts directly from the website. Something similar to Loomly, Sprout, or Hootsuite, but I’m mainly looking for something that’s more cost-efficient. I came across OneUp AI, but I want to explore other options that fit my budget. Here’s what I’m looking for: Ability to post to 9-10 different accounts Schedule posts in advance (I’d prefer no strict limits, but something like 100 is fine) Main platforms I need to post to are TikTok, Instagram Reels, and YouTube Shorts No need for extra gimmicks, just simple and easy scheduling I’m not looking for free trials; I’m willing to pay, but I want to find the cheapest option that still meets these needs. Sorry, I know there are a lot of posts like this, but I couldn't find one that focused on being affordable while meeting my specific criteria. Any recommendations would be appreciated! Thanks! submitted by /u/Exciting_Committee85 [link] [comments]
Hey marketers! 🚀 If you’re looking to optimize your ad strategy across platforms like Google, Meta, TikTok, and LinkedIn, I’ve got some exciting news! Datarise has launched the Social Media Ad Library API, giving you comprehensive access to ad data from major social and digital platforms in one place. Use it for: Market Research: Dive into data by region and platform for insights into consumer behavior. Competitive Analysis: Peek into your competitors' ad strategies and performance. Ad Strategy Optimization: Fine-tune your campaigns with detailed insights on ads and advertisers. Key features include: Multi-platform insights (Google, Meta, TikTok, LinkedIn) Ad performance and advertiser details Search functionality to find ads/pages quickly Would love to hear your thoughts on how you'd use this for your campaigns! submitted by /u/omarmhaimdat [link] [comments]
Gonna be honest here, I'm a dev who needs some motivation. Kinda burned up working on random BS. Really wana build stuff that might help people. If you have any problem that you feel could be solved by software hit me up and I'll build it for free 🙂 submitted by /u/modern_tragedy69 [link] [comments]
Hey so I got my degree in Advertising with a minor in video/photo production. I’m now in a marketing job kicking myself for not doing a marketing major. Realistically how much overlap can I aspect from advertising knowledge to a marketing position? Should I go back to school? submitted by /u/145stanfan [link] [comments]
I own an accounting company with a brand name that isn't specific to an industry. I have recently discovered an industry that isn't heavily marketed too that I'd like to target. I was able to buy the domain ("industry name"accounting.com) Should I create a whole new website for that domain or just redirect that domain to my current website with a landing page? I'd create the landing page to be specific to that niche but if they peaked up at the top URL, they'd notice it was different. Personally, the second option appeals more to me from a management / financial stand point since I won't have to pay for second hosting, building a whole new website, separate blogs, multiple logins, etc. but I ultimately want to do what's best! submitted by /u/ConstantineAccountin [link] [comments]
I've been working on a Reddit growth automation tool called RedditFlow and we’re launching a feature that could be pretty useful for people marketing on Reddit. It uses AI to write posts that follow each subreddit’s rules, while also subtly mentioning your product or business in a way that won’t get you banned. It’s designed to help you stay compliant and even go viral by crafting posts based on what works best in each subreddit. What do you think? Would this be helpful for you? submitted by /u/No-Definition9329 [link] [comments]
Here is where imagination can go wild )) What kind of creazy marketing campaign might be done for interactive AI Agents Market Landscape map? Source AI Agents Directory submitted by /u/DifficultNerve6992 [link] [comments]
We’ve been talking a lot about AIO, and it makes sense for us in the industry. But what about the clients? I’ve got a few big ones in the US who started prepping for the AIO rollout months ago. They’re staying on top of things, and now everything’s going smoothly for them. But I’ve noticed that a lot of my European clients see AIO as something way off in the future. They never bring it up, focusing only on the usual SEO metrics and results. But at the same time, many of them are optimizing their sites for English. When I’ve brought up AIO and what’s coming down the line, they don’t take it seriously. The most common response is, “We’ll deal with it when it gets to our region, right?” Fair enough, but as website owners, I feel like they should be paying more attention to possible future changes in the SERPs. Something about that seems off to me. What’s your experience been like? \I'm in SEO. I've been trying to gather feedback from different communities, but the information is still pretty limited. Maybe the global marketing community can help me figure out how to shape future strategies with my clients. Thanks* submitted by /u/robertgoldenowl [link] [comments]
I've heard from some people that email marketing is dead, especially for B2B businesses, but I'm not fully convinced and that we should create content in social media instead. I work for a software company and we're considering ramping up our email marketing efforts. I read somewhere that B2B businesses should expect email marketing to bring in at least a third of their total sales. If businesses do reach this goal, I'd like to know how they are doing it so maybe we can learn from them, and I can finally say to those who doubt it that email marketing is not dead for B2B. What has been your experience with email marketing lately, particularly in the B2B space? Is it still a valuable channel for your business? Have you found any strategies that work particularly well for reaching other businesses via email? submitted by /u/conventionseeker [link] [comments]
I was laid off from my B2B SaaS role this summer, despite driving some fantastic results with SEO and content marketing. Typically, I've been able to land new opportunities quickly, but this time feels different. In the first few weeks of unemployment, I was getting interviews, but lately, the responses have slowed, and it's starting to worry me. Over the past couple of years, I’ve gone through a bit of an existential crisis. I fell in love with digital marketing when I started in 2017, but there are days when I wonder if I chose the wrong path (I was considering grad school, and sort of fell into this field by accident). I’m still passionate about helping companies grow through content and SEO, but many seem increasingly reluctant to invest in it. If anyone is looking for a US-based full-stack marketer with expertise in SEO and content strategy, I’d love to connect. I promise you won't regret it! Advice is welcome, too. If you made it this far, thanks for reading this. submitted by /u/growthhacker4893 [link] [comments]
I'm a week and a bit into my new job as a marketer. The company sells specialist building tools and equipment. I've been trying my hardest to push out content for the company to use. Yesterday I had my first training session on our products and was asked to tailor my content to that. I've already been pulled into the office twice (today) about my work not being good enough. I've been told I should be able to do the task and that he's worried I won't be able to cope when I get more tasks. That's despite being told the expectations were low at interview. How do I approach this? Is it unusual for an employer to put so much pressure on in the second week. submitted by /u/Final-Perception3636 [link] [comments]
So! This discussion came to the table one time we were talking about Kotler's Marketing Mix during a Sales Focused Marketing class I was having back when I was studying tourism. As we all know the original "3P" setting that Kotler proposes are: Product, Price and Place. Product: This encompasses everything related to the actual offering, including its design, features, branding, packaging, and overall customer value proposition. Price: This covers the financial aspects of the marketing exchange, including the pricing strategy, discounts, payment terms, and how the pricing aligns with the perceived value of the product. Place (or Placement): This focuses on how the product reaches the customer, encompassing distribution channels, logistics, inventory management, and the physical or virtual locations where the product is available. We called th se either the “Marketing Mix” or “Kotler's 3P” as well, even in exams. One day I was having a headache with their assignment we were given of making an imaginary product that we would try to put out into the market and sell, I remember mine being something dumb like a tea cup with a warmer or something like that. And si was having a LOT of problems with the Place AKA Placement part. Because I found out that to me this part of the Marketing Mix was too overcrowded in comparison to the Product and Price part of the assignment, the Product section being a basic description of the tea cup and how it worked, the packaging, the designs and such; price a small essay on how does the pricing work decided for an approach where I would start selling at a price to actually compete with normal tea cups, at the costs of not earning more than 10% per cup slowly increasing over time along with sales in a steady and organic way; and finally when it came to placement I found myself sooner than nothing drowned between logistics and the actual marketing part of the product where the communications and activities for the positioning of the product takes place. So I found myself sooner than later thinking of a solution for myself, I separated Kotler's proposed 3P and added a 4th one. It was in 2017 something like 7 years ago when I came up with this idea but I remember the justification part of my essay being something along the lines of: Product: This refers to the actual good or service being offered. It includes aspects like features, branding, packaging, and quality. Price: This is the amount of money customers pay for the product. It involves setting the right price point, discounts, payment terms, and pricing strategies. Place (or Placement): This refers to how the product gets to the customer. It includes distribution channels, logistics, inventory management, and location decisions. Promotions: This covers all the communication and marketing activities used to inform and persuade customers to buy the product. It includes advertising, public relations, sales promotions, personal selling, and digital marketing. The basic idea was basically separating placement from promotions, because the logistics to me can be considered a different step than the background marketing, and being assessed separately means there's more room for thorough thought along the line, also as an strategy to focus resources more accurately. All in all I got a 10/10 in that assignment, which was like 90% of the Sales Focused Marketing class I was taking, literally had to nothing else to have a final score of 9/10 at the end of the semester. -------- [EDIT]: I know it seems like I am suggesting the idea for the 4th P was mine, truth be told it was suggested by my teacher and the 4th P format it's Kotler's own doing. English ain't my first language so I am prone to committing to those mistakes when typing. Am just trying to open discussion to the benefits of using the 4P format over the 3P format. At the time I didn't knew of the 4P format cause we were using Kotler's old 1967 edition of the "Marketing Management: Analysis, Planning, and Control" book, and bits and pieces of it at that. And I was trying to portal how much of a mind-blow was to discover that you could talk about Placement and Promotion separately. And how I was the only one using that format and getting a 10/10 in that assignment, my teacher suggested the use of the 4th P at some point. I have been observing that many universities use the 3P format as well to teach their students, dunno if it's for the sake of simplicity or what but found it interesting to discuss just that and how one way while more complex it's simpler on the analysis and keeping data better separated. submitted by /u/EnZeeeRu [link] [comments]
How do you deal with ambitious marketing ideas vs limited budgets? What’s your hack? Asking for a friend. submitted by /u/Professor_Pink007 [link] [comments]
How do you increase interactions on reddit? How are reddit's ads run? How do I get conversions from my reddit accounts and from Facebook? submitted by /u/Fleek_papers [link] [comments]
SEO Audits: Building a Website Recovery Roadmap After Google Updates
Hey there, Reddit’s largest Marketing community! Given that most of you work with clients’ websites, we believe that insights into website audits would be super valuable here. Today, we’re going to share some highlights from our conversation with Olga Zarr, the Founder & CEO of SEOSLY. She’ll be sharing her expertise on performing SEO audits for digital businesses and agencies, especially in light of recent Google updates. Off we go!
Host:We know that Google updates (like the recent helpful content updates, spam, and two core updates that were rolled out within the last two months), are really shaking things up for different websites. What would you tell to people who are wondering how Google updates can affect their website’s performance? Guest:There are three types of scenarios. 1.) The first one is you aren’t affected at all, which I noticed in the case of websites where I really don’t do any tricks. I just publish content based on SEO fundamentals. Those types of websites usually are not affected by core updates. 2.) There is of course the possibility of a very positive effect, which means that Google changed something they value and now you have this thing present. You are using it to like 100%. And then you can experience a traffic spike. 3) There can also be a negative outcome where you basically lose traffic because Google is now valuing something you don’t have.
Host:What if we go for the second scenario, and you see a traffic drop or ranking decrease and you know that a Google update was just recently released? What is the first thing you suggest to do to figure out what went wrong for your specific website? Guest:The most important thing is to not do anything. Wait until the update is finished and then take a close strategic approach in really assessing who is now ranking above you and how they differ from your site. [Look at] what they have that you don’t have.
Host:Do you analyze on page, off page, technical… what do you look at? Guest:When I land new clients, or when someone comes to me because they lost traffic and they need a traffic drop analysis, what I always suggest doing is a full SEO audit. Analyze the site from all possible angles, meaning on page, off page, technical, content… Everything. [I look at] the full package.
Host:Is there anything that you do to automate the process? Guest:For example, when I start the audit, I spend 30 minutes or so just playing with the website; opening it on my phone, browsing it, clicking, trying to add things to cards, adding some filters, just seeing how the site works. And there’s an automatic part where I have to crawl the sites. So that I have all the URLs, all the images extracted, everything, JavaScript executed… So that I can see everything from the technical side. I can see the size of the site, the status codes… all those types of things. You have to use the tools intelligently but still rely on your own human element, the human brain.
Host:Could share your experience in terms of what you look at specifically? Guest:I have my own template (It’s public, I share it on my website). I think there are 288 points or something… then I go into Google Search Console and review every report there (and also Google Analytics). And these are the first three things I do, and then I follow the checklist which usually then starts with technical things like robots, text, sitemaps, titles, and other things like that.
Host:How do you decide the priority of which issues need to be fixed? Guest:Generally, you want to divide the issues; like their priority, and their urgency, and how easy it is to implement them. Because sometimes it may, in the case of a huge e-commerce site, getting one small thing done, which is not really that important, may take months. But there may be smaller things you can do, which will take a shorter period of time, and they can have a bigger impact. So you need to assess what issues are critical, and are harming SEO right now. So this usually has to be taken care of in the first place. Then I always try to identify some quick SEO wins (as a bonus) so that potentially the client can see some positive results sooner than later, because usually SEO takes a lot of time. […] I got clients saying that they are not visible in Google for their brand name. They wanted me to do branded type of research: what’s going on, why their brand is not showing up, etc. And the first thing I do, I realize that they have no index tag on their site. It is not the problem with their brand, but their site is blocked from indexing. So without solving this one thing, there is no point in doing anything else.
Host:I wanted to get your thoughts… For example, you have 10 clients, you have your own website, and you need to take care of everybody’s audit. How do you manage that process? Guest:You have to use a task management program. You can create those processes there; what step needs to be taken as the first one, the second one, and you simply train your SEOs. Simply follow them, and this way, you can just review their work instead of doing it by yourself. It’s scalable. And don’t forget about automatically reviewing and alerting using specialized tools.
And there you have it. These insights should help your SEO agency thrive and improve your processes with clients. Each of the points presented above were handpicked specifically to help you build your website auditing and prioritization workflow. I hope you guys also enjoyed these highlights. And don’t hesitate to share your thoughts in the comments section below. Our team wishes you a profitable Q4 and the best of success in all your marketing projects!
15 powerful “psychological tricks” to increase your sales💰
Sell your freemium as LTD. If your audience is price-sensitive like SMBs or freelancers, you might want to convert your freemium into LTD where they have to pay for lifetime access once, and once they’re in upsell them a subscription.
Price Anchoring: Use comparative pricing to show the value of your offer, making your product more attractive price-wise.
Leverage Social Proof: People base their purchasing decisions on others’ experiences. Highlight reviews and testimonials in your marketing to show that your product is trusted and valued by people similar to your ICP.
Solicit Genuine Reviews: Encourage your satisfied customers to leave honest reviews. This not only provides social proof but also counters any skepticism about the authenticity of the reviews.
Offer Free Trials or Demos. PLG for the win. Let customers to test your product without commitment can be a major a decisive factor in their decision to purchase.
Offer Limited Choices: Too many options will overwhelm your prospects. Limit their choices just enough so they feel like they are making the decision.
Address the Fear of Making the Wrong Decision: Providing options like money-back guarantees can reduce the perceived risk and encourage purchases, despite the actual usage of such guarantees being low.
Utilize Scarcity and Urgency(but don’t fake it). Indicate limited availability or time-sensitive offers to create a sense of urgency, prompting quicker purchasing decisions.
Brand Familiarity: Build brand awareness through repeated exposure. Familiar brands are often trusted more, leading to higher chances of purchase.
Reduce Cognitive Load: Simplify information and choices to avoid overwhelming potential customers, making it easier for them to decide.
Create a Ceremony Around Pricing: For B2B or high-value products, making customers wait for a quote can signal quality and thoughtfulness, as well as increase perceived value.
Use Clear Calls to Action (CTAs): Guide customers on what to do next with clear and specific instructions.
Target a ‘Starving Crowd’: Identify and cater to a market with a strong, existing need for your product or service.
Tailor Messaging to Audience Expectations: Understand the stereotypes or assumptions your target audience might have about your product or industry. Craft your marketing messages to align with these perceptions positively. For instance, if you’re marketing a luxury product, your audience might assume high quality and exclusivity, so your messaging should reinforce these ideas.
Challenge Negative Perceptions: If your product or industry suffers from negative stereotypes, use your marketing to challenge and change these perceptions. For example, if you sell a product that’s traditionally seen as low quality or cheap, focus on showcasing its unexpected durability or high-end features.
Marketing begins and ends with measurement. Here’s how to make sense of it all
We’re in a watershed moment for advertising.
Expanded regulations are shifting the privacy landscape, as consumers demand more transparency and control over their data. And platform updates — like Chrome’s plans to deprecate third-party cookies in the second half of 2024 — require businesses to adopt more durable ways to meet their marketing objectives and drive business growth. Then there’s the rapid evolution of newer technologies, including AI.
Disruption isn’t new to marketers, but this time around, it’s particularly profound. Because, while the fundamentals of marketing haven’t changed, how you achieve your goals is changing dramatically.
At Google, we’re building products and services to help you navigate this transition with confidence, and we believe that confidence begins with measurement. Without a firm grasp of the signals you use to achieve your goals, you’re driving without a map. With the proper data and a strong marketing measurement foundation, you can see clearly what’s working and make adjustments.
In our current context, this can still feel daunting. Here’s the good news: The steps toward a strong measurement foundation enable you to take advantage of AI opportunities. Used together, these components will help you make decisions with confidence and power AI to deliver long-term performance for your business. But taking action is easier when you start by asking the right questions.
We’ve thought through and answered three critical measurement considerations. We hope they provide you with confidence as you prepare for 2024. Let’s start by addressing the elephant in the room.
How can I effectively measure my campaigns’ success in a post-third-party cookie world?
Until recently, cookies and other identifiers would automatically capture signals to help marketers better understand their customers. These capabilities weren’t built with privacy in mind, however, and they are gradually being phased out.
While 90% of marketers say that first-party data is important to their digital marketing, just 1 in 3 claim to be using it effectively.
As a marketer, your best response to the departure of third-party cookies is a strong foundation of first-party data. This data, established from meaningful connections you make with your customers, is decisive information for Google solutions. Once you have a strong foundation, Google AI works to deliver insights and find new customers, no matter the kind of data you enter, be it website interactions, purchase history, or profit. This means you can get accurate conversion measurement while also fueling AI with high-quality information.
First, set your goals. Then, as you uncover insights and make adjustments, AI will learn from you. And, because your business owns this data, you have full control over how it’s used and collected. Any collection of data should, above all else, build customer trust in your brand and help you meet people’s needs.
Unfortunately, for many, first-party data is often fragmented, unstructured, and scattered across many different systems within a business, including customer relationship management, data storage systems, and customer data platforms. Indeed, while 90% of marketers say that first-party data is important to their digital marketing, just 1 in 3 claim to be using it effectively.1
Proper sitewide tagging is essential to effectively measure and act on your data.
Effectively capturing first-party data and organizing it to work for specific business needs can be challenging to do on your own. That’s why we’ve introduced solutions like Google Ads Data Manager, which simplifies data management, making it easier to measure conversions and reach people with relevant ads.
Beyond prioritizing a first-party data strategy, what’s the first privacy-preserving tool I should adopt?
Sitewide tags are fundamental to a strong measurement foundation. They help marketers ingest high-quality first-party data to understand how customers are interacting with their brand online.
Historically, it’s been difficult to set up and manage website tags without technical expertise or a tag management platform, like Google Tag Manager. To address this, we introduced a single, reusable Google Tag that helps marketers do more across different Google products and accounts without changing their website code. Since then, we’ve rolled out additional tagging capabilities that simplify a website’s setup and provide more visibility into the measurement coverage.
Whether it’s through the Google Tag or Tag Manager, proper sitewide tagging is essential to effectively measure and act on your data. One company that has shown measurement excellence through tagging is The North Face.
The North Face uses Google Tag Manager to capture the full spectrum of consumer behavior, turn those signals into insights, and then measure the behavior. This enables the company to adjust its marketing in near real-time and better serve customers. It’s driving conversions and growing revenue as a result.
Bethany Evans, The North Face’s VP of Americas marketing, explained how Tag Manager helped her team keep up with the latest emerging search terms for products they sell. Armed with that information, the team would rename their products to ensure consumers could find what they are looking for online. “We were able to quickly rename our products and make sure that our search functionality was working on the website to serve up that information, and we saw, essentially, a tripling overnight in both conversion and revenue, because people were able to find what they were looking for.”
Beyond website tags, there are several other existing tools ready to be put to work. Explore our AI Essentials for a comprehensive list.
What is the relationship between my first-party data and AI, and does it prioritize privacy?
AI technologies are only as good as the information they’re fed. The higher quality the information input, the better the output. For some, this information could be time spent on your website and app installations; others may focus on revenue and purchase history. And since you know your customers and campaign goals best, training AI on those insights means connecting the signals that matter most to your business — whether that’s an increase in conversions or acquiring high lifetime value customers.
First-party data acts like premium fuel for AI tools — a high-quality input that generates better output. And while some advertisers worry that fueling AI with their first-party data will result in them losing control over both, that’s not the case.
Here’s why. We do use aggregated conversion data for the overall benefit of advertisers, such as to understand whether a customer is more likely to convert. This aggregated data plays a crucial role in improving bidding and detecting spam and fraud. We ensure that individual advertiser data remains fully protected, while employing durable measurement and audience solutions.
First-party data acts like premium fuel for AI tools — a high-quality input that generates better output.
All AI algorithms train on large data sets, which is what, given the right information, makes them so reliable. But remember, it takes time for AI to learn. The sooner you begin working with AI, the sooner it can benefit your bottom line. Already, we are seeing many companies thoughtfully assess their business performance indicators to deliberately build their organizations in a way that enables agile work geared toward specific-business needs.
A powerful example of an advertiser using the strength of first-party data together with AI to achieve impressive results is Dutch bicycle company Swapfiets. A subscription-based business, one of Swapfiets’ biggest challenges is growing a new customer base. To address it, the company tapped into Google AI by combining Performance Max’s new customer acquisition goal with its online and offline Customer Match data. Swapfiets saw a 36% increase in new customer transactions. Because of this result, the new customer acquisition goal is now part of Swapfiets’ always-on campaign across all of its markets.
Prepare for tomorrow, today
It’s easy to feel overwhelmed in today’s marketing ecosystem, but building a strong measurement foundation — by prioritizing high-quality data, leveraging durable tag solutions, and embracing AI — can increase your confidence and put you on the path to better business outcomes. If you haven’t started adopting AI, check out the AI Essentials. Then prepare for a future without third-party cookies to protect your measurement and drive business growth in 2024.
How Subway maximizes the impact of marketing mix modeling to drive growth
Just a few years ago, marketing mix modeling seemed to be fading in importance. Many considered it a relic of predigital times, with a limited ability to generate actionable insights and recommendations. But recent innovations have made marketing mix models (MMMs) far more nimble. When taken together with the inherent privacy durability of MMMs and their ability to measure all marketing spend on a level playing field, these innovations suggest marketing mix models have a bright future in our industry.
At Subway®, MMMs are integral to our cross-media measurement strategy and help us to evaluate the effectiveness of our marketing and media investments. In an effort to further hone our approach, we enlisted our partners at Ipsos MMA and Google to help us navigate an increasingly complex consumer landscape and allocate spend accordingly.1 Here are some of our key learnings.
1. Develop more granular insights
With the fragmentation of digital advertising across media and ad formats, devices, market areas, and bid strategies, marketers must be cautious not to oversimplify their measurement frameworks. At Subway, we have recommitted to capturing granular insights in order to figure out which channels and ad types represent the smartest investment and to make more informed decisions.
Layering bumper ads on top of TrueView ads drove 2X higher ROI than running TrueView alone.
Thankfully, digging into these details is easier than ever. We can now understand important drivers of platform performance and evaluate the role of new channels and formats in a way that wasn’t possible in the past.
In partnership with Google and Ipsos MMA, Subway has been able to isolate the impact of various types of campaign-level marketing data and integrate those insights into our model. For example, we learned that layering bumper ads on top of TrueView ads drove 2X higher ROI than running TrueView alone, and that sequencing video ads proved 20% more effective than YouTube’s average performance metrics.2
These measurement strategies and capabilities, once unthinkable in marketing mix modeling, have helped Subway see both the forest and the trees when allocating marketing investments.
2. Consider long-term effects
MMMs typically account for the effects of advertising months after initial exposure. But what about measuring its compound effect over a period of years? Many marketers will prioritize quick wins and short-term gains when money is tight, but it’s critical not to lose sight of your brand’s long-term health.
While collaborating with Google and Ipsos MMA, we wanted to examine the impact of advertising over a lengthy time period. So we ran a long-term effects model that applied key brand health metrics, such as unaided awareness, consideration, and familiarity.
The results were clear: Investing in digital is an effective way to increase brand health metrics. Due to our strategic adjustments, Subway’s return on ad spend for online video has increased 1.8X since 2021.3
3. Lean into multiple data sources
Data is essential for driving meaningful organizational change. We use multiple data points to make informed decisions about our marketing strategy and achieve better results for our franchisees.
For example, we used Google’s Reach Planner to understand the reach and frequency dynamics of our advertising on YouTube and linear TV. Reach Planner revealed that we were reaching our target audience 3.5X more per month on TV relative to YouTube.4 This insight into relative frequency played a pivotal role in shaping the qualitative metrics that guided our interpretation of our MMM results.
Then we uncovered another astonishing insight: YouTube on connected TV (CTV) was 2X more effective than other devices.5 These complementary data points gave us the confidence to increase Subway’s YouTube, streaming, and overall digital presence by more than 50%. The business results spoke for themselves. By leaning into these learnings, our business saw 10 consecutive quarters of sales growth.
While we’ll always value TV’s role in our media plan, the data we uncovered helped us better understand its contribution relative to other channels.
An actionable marketing mix model requires organizational readiness
Of course, implementing all of the above into your marketing strategy is easier said than done. Feeding nuanced insights into your MMM and acting on its output may require significant organizational changes at your company.
This is exactly the challenge we faced at Subway, and we tackled it one step at a time.
First, we aligned stakeholders on KPIs and our measurement strategy, ensuring everyone was on the same page for consistency and efficiency. While this may seem straightforward, achieving cross-functional alignment can be daunting.
MMMs will be a critical tool in helping brands to understand the micro and macro shifts that impact performance.
For instance, while some decision-makers evaluate operating costs and efficiencies across the marketing organization, others must prove the impact of their budgets. If they want to make the best decisions for their business, both must align on their objectives and believe in measurement and data. Achieving this alignment means ensuring stakeholders are comfortable with how a marketing mix model works and overcoming any fears they may have. It’s important to explain what MMMs can and can’t do for your team.
We also realized that we needed a more holistic approach to measurement. In the past, traditional media and digital media were often siloed, with different teams responsible for measuring and analyzing each. After breaking down the silos, we better understood how these channels complement each other. While having a single team evaluate every type of media may seem incredibly complicated, in reality it’s simple. No matter the medium, we see what works the best, maximizing ROI, traffic, and revenue with the budget we have.
At Subway, we’re always trying to answer one question: How do we take our franchisee’s dollars and invest them in media that will drive money back to the franchisees? Rethinking our MMM strategy has helped us get closer to that goal. As a brand with 60 years of experience, we know that consumer trends and consumption habits are constantly evolving, especially among younger generations. Going forward, we believe that MMMs will be a critical tool in helping brands to understand the micro and macro shifts in marketing behaviors that impact performance on any time horizon.
Unraveling August 2023: Spotlight on Generative AI, Tech, Sports and the Month’s Hottest Trends.
Welcome to the hub of the most intriguing and newsworthy trends of August 2023! In this era of rapid development, we know it’s hard to keep up with the ever-changing world of ai, technology, sports, entertainment, and global events. That’s why we’ve curated this one-stop blog post to provide a comprehensive overview of what’s making headlines and shaping conversations. From the mind-bending advancements in artificial intelligence to captivating news from the world of sports and entertainment, we’ll guide you through the highlights of the month. So sit back, get comfortable, and join us as we dive into the core of August 2023!
OpenAI has released a guide for teachers using ChatGPT in their classroom. This guide includes suggested prompts, explanations about ChatGPT’s functionality and limitations, as well as insights into AI detectors and bias.
The company also highlights stories of educators successfully using ChatGPT to enhance student learning and provides prompts to help teachers get started. Additionally, their FAQ section offers further resources and answers to common questions about teaching with and about AI.
OpenAI’s teaching with AI empowers teachers with resources and insights to effectively use ChatGPT in classrooms, benefiting students’ learning experiences. While Competitors like Bard, Bing, and Claude may face pressure to offer similar comprehensive guidance to educators. Failing to do so could put them at a disadvantage in the increasingly competitive AI education market.
Meta announced 2 new AI updates: DINOv2, FACET (FAirness in Computer Vision Evaluation)
Meta has announced the commercial relicensing and expansion of DINOv2, a computer vision model, under the Apache 2.0 license to give developers and researchers more flexibility for downstream tasks.
Meta also introduces FACET (FAirness in Computer Vision Evaluation), a benchmark for evaluating the fairness of computer vision models in tasks such as classification and segmentation. The dataset includes 32,000 images of 50,000 people, with demographic attributes such as perceived gender age group, and physical features.
Why does this matter?
FACET ensures more equitable experiences when interacting with computer vision technology, reducing the risk of bias based on demographics. On the other hand, DINOv2’s availability under the Apache 2.0 license as it empowers developers and researchers to create more versatile computer vision applications.
The Graph of Thoughts (GoT) framework improves the capabilities of LLMs by modeling information as a graph. LLM thoughts are represented as vertices, and edges represent dependencies between these thoughts. GoT allows for combining thoughts, distilling networks of thoughts, and enhancing thoughts using feedback loops.
It outperforms other paradigms like Chain-of-Thought or Tree of Thoughts (ToT) in various tasks, increasing sorting quality by 62% and reducing costs by over 31%. It is also extensible, allowing for new thought transformations and advancing prompting schemes.
This advancement brings LLM reasoning closer to human thinking and brain mechanisms such as recurrence, both of which form complex networks. It makes AI models more versatile and adaptable, with implications on various domains.
Google announced a slew of massive AI updates at the Google Cloud Next 2023 event. Here are some key announcements:
Vertex AI extends enterprise-ready generative AI development with new models and tooling. Google Cloud gets a curated collection of models across first-party, open-source, and third-party models, including Meta’s Llama 2 and Code Llama, Falcon, Anthropic’s Claude 2, and more. Google’s foundation models– PaLM, Codey, and Imagen– also get several updates.
Powered by DeepMind, a new tool called SynthID helps watermark and identify synthetic images created by Imagen.
Google is expanding its AI-optimized infrastructure with the general availability of Cloud TPU v5e and Nvidia-powered A3 VMs.
Duet AI in Workspace (aiding tasks across meetings, documents, Google Chat, Gmail, and more) is now generally available, and Duet AI in Google Cloud (to assist in code refactoring, improving, etc.) is expanding its preview and will be generally available later this year
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Duet AI in Google Cloud also includes advancements for software development, application infrastructure and operations, data analytics, accelerating and modernizing databases, and security operations.
Search Generative Experience (SGE) launches in the first countries outside the U.S. — India and Japan (with multilingual and local language support).
Why does it matter?
The advancements seem to offer a complete solution for AI, from computing infrastructure to end-to-end software and services that support the full lifecycle of model training, tuning, and serving at global scale. It will help organizations harness the full potential of AI with data and cloud through a unified foundation.
Introducing Zapier AI Chatbot: Create custom AI chatbots with no code
Now you can build your own AI-powered chatbot through Zapier Interfaces, its no-code, automation-powered app builder currently in beta. You also have a variety of sharing options, so you can embed chatbots on your website or limit access to your team or external stakeholders.
The base AI Chatbot model is GPT-3.5. With Interfaces Premium, you can connect to other models (like GPT-4) using an API key from your personal OpenAI account.
Why does this matter?
This makes it easier for businesses and individuals to create custom AI chatbots, no coding required. It democratizes AI chatbot development, potentially increasing their accessibility across various industries/applications and fostering innovation in AI.
Meta researchers find AI “Déjà Vu”ing: Suggested ways to address the privacy risks; Meta’s ImageBind: The ultimate fusion of 6 data types in 1 AI model; Meta’s Sandbox: Where AI meets advertising; Meta bets big on AI with custom chips & a supercomputer; Meta scaling Speech Technology to 1,100+ languages; Meta’s MusicGen: The LLaMA moment for music AI; Meta disclosed AI behind Facebook and Instagram recommendations; Meta merges ChatGPT & Midjourney into one; Meta unveils Llama 2, a worthy rival to ChatGPT; Meta-Transformer lets AI models process 12 modalities; Meta collabs with Qualcomm to enable on-device AI apps using Llama 2; Meta’s AudioCraft is AudioGen + MusicGen + EnCodec; Meta challenges OpenAI with code-gen free software; Meta’s SeamlessM4T: The first all-in-one, multilingual multimodal AI; Meta to rival GPT-4 with a free Llama 3?
Meta researchers find AI “Déjà Vu”ing: Suggested ways to address the privacy risks
Researchers at Meta recently discovered an anomaly common across most Self Supervised Learning (SSL) algorithms and call it Déjà Vu. They said SSL models can unintendedly memorize specific parts in individual training samples rather than learning semantically meaningful associations.
The report shares the details of studies around this unintended memorization and also explores ways of avoiding it.
Meta’s ImageBind: The ultimate fusion of 6 data types in 1 AI model
Meta has announced the new open-source AI model called ‘ImageBind’ that links together multiple data streams- text, audio, visual data, temperature, and movement readings. ImageBind is the first to combine 6 data types into a single embedding space.
The company also notes that other streams of sensory input could be added to future models, including touch, speech, smell, and brain fMRI signals.
Meta’s Sandbox: Where AI meets advertising
Meta has introduced an AI Sandbox for advertisers, which includes features such as alternative copy generation, background creation through text prompts, and image cropping for Facebook or Instagram ads. This new tool aims to assist advertisers in creating more diverse and engaging content using AI.
The tools are still in beta, but they have the potential to revolutionize how ads are created and delivered.
Meta bets big on AI with custom chips & a supercomputer
Meta is making a big bet on AI by developing custom chips and a supercomputer. The company is developing its own chips called the Meta Training and Inference Accelerator (MTIA), which will be optimized for AI workloads and allow for more efficient training and running of complex models.
In addition, Meta is building a supercomputer, which will be used to train large-scale AI models for natural language processing and computer vision. These investments aim to enable the development of more advanced products and services, such as virtual assistants and augmented reality applications.
Meta scaling Speech Technology to 1,100+ languages
Meta’s Massively Multilingual Speech (MMS) project aims to address the lack of speech recognition models for most of the world’s languages, introduced Introducing speech-to-text, text-to-speech. Combining self-supervised learning techniques with a new dataset containing labeled data for over 1,100 languages and unlabeled data for nearly 4,000 languages.
The MMS models outperform existing ones and cover 10 times as many languages. The project’s goal is to increase accessibility to information for people who rely on voice as their primary means of accessing information. The models and code are publicly available for further research and development. The project aims to contribute to the preservation of the world’s diverse languages.
Meta’s AI Segmentation Game Changer
Meta’s researchers have developed HQ-SAM (High-Quality Segment Anything Model), a new model that improves the segmentation capabilities of the existing SAM. SAM struggles to segment complex objects accurately, despite being trained with 1.1 billion masks. HQ-SAM is trained on a dataset of 44,000 fine-grained masks from various sources, achieving impressive results on nine segmentation datasets across different tasks.
HQ-SAM retains SAM’s prompt design, efficiency, and zero-shot generalizability while requiring minimal additional parameters and computation. Training HQ-SAM on the provided dataset takes only 4 hours on 8 GPUs.
Meta plans to put AI everywhere on its platforms
Meta has announced plans to integrate generative AI into its platforms, including Facebook, Instagram, WhatsApp, and Messenger. The company shared a sneak peek of AI tools it was building, including ChatGPT-like chatbots planned for Messenger and WhatsApp that could converse using different personas. It will also leverage its image generation model to let users modify images and create stickers via text prompts.
META released MusicGen, a controllable music generation model for producing high-quality music. MusicGen can be prompted by both text and melody.
The best thing is anyone can try it for free now. It uses a single-stage transformer language model with efficient token interleaving patterns, eliminating the need for multiple models.
MusicGen will generate 12 seconds of audio based on the description provided. You can optionally provide a reference audio from which a broad melody will be extracted. Then the model will try to follow both the description and melody provided. You can also use your own GPU or a Google Colab by following the instructions on their repo.
Meta’s new human-like AI model for image creation
Meta has introduced a new model, Image Joint Embedding Predictive Architecture (I-JEPA), based on Meta’s Chief AI Scientist Yann LeCun’s vision to make AI systems learn and reason like animals and humans. It is a self-supervised computer vision model that learns to understand the world by predicting it.
The core idea: It learns by creating an internal model of the outside world and comparing abstract representations of images. It uses background knowledge about the world to fill in missing pieces of images, rather than looking only at nearby pixels like other generative AI models.
Captures patterns and structures through self-supervised learning from unlabeled data.
Predicts missing information at a high level of abstraction, avoiding generative model limitations
Delivers strong performance on multiple computer vision tasks while also being computationally efficient. Less data, less time, and less compute.
Can be used for many different applications without needing extensive fine-tuning and is highly scalable.
Meta’s all-in-one generative speech AI model
Meta introduces Voicebox, the first generative AI model that can perform various speech-generation tasks it was not specifically trained to accomplish with SoTA performance. It can perform:
Text-to-speech synthesis in 6 languages
Noise removal
Content editing
Cross-lingual style transfer
Diverse sample generation
One of the main limitations of existing speech synthesizers is that they can only be trained on data that has been prepared expressly for that task. Voicebox is built upon the Flow Matching model, which is Meta’s latest advancement on non-autoregressive generative models that can learn highly non-deterministic mapping between text and speech.
Meta disclosed AI behind Facebook and Instagram recommendations
Meta is sharing 22 system cards that explain how AI-powered recommender systems work across Facebook and Instagram. These cards contain information and actionable insights everyone can use to understand and customize their specific AI-powered experiences in Meta’s products.
Moreover, Meta also shared its top ten most important prediction models rather than everything in the system to not dive into much technical detail can sometimes obfuscate transparency.
Using an input audio sample of just two seconds in length, Voicebox can match the sample’s audio style and use it for text-to-speech generation.
Meta plans to dethrone OpenAI and Google
Meta plans to release a commercial AI model to compete with OpenAI, Microsoft, and Google. The model will generate language, code, and images. It might be an updated version of Meta’s LLaMA, which is currently only available under a research license.
Meta’s CEO, Mark Zuckerberg, has expressed the company’s intention to use the model for its own services and make it available to external parties. Safety is a significant focus. The new model will be open source, but Meta may reserve the right to license it commercially and provide additional services for fine-tuning with proprietary data.
Tesla is launching its highly-anticipated supercomputer today. The machine, employing 10,000 Nvidia H100 compute GPUs, will be used for various AI applications. It is said to be one of the most powerful machines in the world.
But NVIDIA is struggling to keep up with the GPU demand. Thus, Tesla is investing over $1B to develop its own supercomputer, Dojo, built on the company’s hyper-optimized custom-designed chip. Tesla is also activating Dojo simultaneously. Take a look at Tesla’s internal forecast for the compute power of Dojo.
Why does it matter?
Elon Musk recently revealed that Tesla plans to spend over $2B on AI training in 2023 and is hiring reputed AI engineers. But this move gives Tesla unparalleled compute power. It also underscores Tesla’s commitment to overcoming computational bottlenecks in AI and should provide substantial advantages over its rivals. Elon might be the next big thing in AI. What do you think?
OpenAI launches ChatGPT Enterprise, the most powerful ChatGPT version yet
Open has launched ChatGPT Enterprise, the most powerful version of ChatGPT yet. It offers enterprise-grade security and privacy, features for large-scale deployments, unlimited higher-speed GPT-4 access, 32K context for faster processing of longer inputs, advanced data analysis capabilities, customization options, and much more. OpenAI is also working on more features and will launch them soon.
Why does it matter?
This is a simple and safe way of deploying ChatGPT into core operations at organizations. It could be a solution for big companies that have banned ChatGPT at work over privacy concerns, like Apple, Amazon, Citigroup, and more. Maybe, this can pave the way for truly widespread adoption of AI in the business world.
Usage of ChatGPT among Americans rises, but only slightly
A recent survey conducted in July by Pew Research Center reveals 18% of U.S. adults have ever used ChatGPT. While 16% of those who have heard of the tool and are employed say they have used it for tasks at work.
The statistic is consistent with a similar survey conducted in March by the Pew Research Center that showed 14% of U.S. adults had tried ChatGPT. And about one in ten working adults who had heard of ChatGPT used it at work.
While this shows increased adoption of ChatGPT among Americans, it is not a significant one in the grand scheme of AI adoption today. In fact, only a few think it will have a major impact on their job.
Why does this matter?
These findings suggest AI’s penetration remains gradual. It is also clear that there is still work to be done in educating and acclimating the workforce to the benefits and implications of generative AI. Plus, given the lingering concerns and uncertainties about ChatGPT’s prowess, maybe it is too early to start worrying about AI replacing jobs.
What Else Is Happening in AI
Microsoft infuses AI with human-like reasoning via an “Algorithm of Thoughts”.
DoorDash launches AI-powered voice ordering to answer calls and curate recommendations.
Uber is working on an AI chatbot for its food delivery app.
Yahoo Mail introduces new AI-powered capabilities, including a ‘Shopping Saver’ tool.
Generative inbreeding, akin to inbreeding in genetics, is a concern as AI systems training on AI-generated content can degrade their performance and distort human culture.
Tesla’s $300M AI cluster is going live today – Tesla is launching its highly-anticipated supercomputer today. The machine, employing 10,000 Nvidia H100 compute GPUs, will be used for various AI applications. – But NVIDIA is struggling to keep up with the GPU demand. Thus, Tesla is investing over $1B to develop its own supercomputer, Dojo, built on the company’s hyper-optimized custom-designed chip. Tesla is also activating Dojo simultaneously.
OpenAI launches ChatGPT Enterprise, the most powerful ChatGPT version yet – It offers enterprise-grade security and privacy, features for large-scale deployments, unlimited higher-speed GPT-4 access, 32K context for faster processing of longer inputs, advanced data analysis capabilities, customization options, and much more. OpenAI is also working on more features and will launch them soon.
Usage of ChatGPT among Americans rises, but only slightly – A recent survey conducted in July by Pew Research Center reveals 18% of U.S. adults have ever used ChatGPT. While 16% of those who have heard of the tool and are employed say they have used it for tasks at work. The statistic is consistent with a similar survey conducted in March by the center. – While it shows increased adoption of ChatGPT among Americans, it is not a significant one in the grand scheme of AI adoption today. In fact, only a few think it will have a major impact on their job.
Microsoft infuses AI with human-like reasoning via an “Algorithm of Thoughts” – The technique guides the language model through a more streamlined problem-solving path. It utilizes in-context learning, enabling the model to explore different solutions in an organized manner systematically. The result? Faster, less resource-intensive problem-solving.
DoorDash launches AI-powered voice ordering service – It will answer calls and provide customers with curated recommendations.
Uber is working on an AI chatbot for its food delivery app – It will offer recommendations to food-delivery customers and help them more quickly place orders.
Yahoo Mail introduces new AI-powered capabilities – The rollout includes upgrades to several of Yahoo Mail’s existing AI features and introduces a new Shopping Saver tool.
Poe by Quora lets you use all the AI chatbots in one place – Its goal is to be the web browser for accessing AI chatbots, and it just got a bunch of updates.
IBM’s new analog AI chip challenges Nvidia
IBM has developed an analog AI chip that’s up to 14 times more energy-efficient than current digital chips, addressing the power-hungry nature of generative AI.
The analog chip’s ability to manipulate analog signals and its human brain-like operation could potentially challenge Nvidia’s dominance in AI hardware.
IBM’s prototype chip demonstrated significant energy efficiency gains, encoding millions of memory devices and modeling parameters while performing computations directly within memory.
AI’s promise and peril in cancer research
UK-based biotech startup Etcembly used generative AI to develop a novel immunotherapy targeting hard-to-treat cancers, demonstrating AI’s potential for medical advancements.
However, risks of AI in healthcare are evident, as a study reveals that AI-generated cancer treatment plans, like those from ChatGPT, contained factual errors and contradictory information.
While AI-powered tools hold promise, their clinical deployment without rigorous validation could lead to dangerous missteps, highlighting the importance of skepticism and human consultation.
Linkedin: Building soft (human) skills remains key in the age of AI
Summary: A new LinkedIn report reveals that AI skills are spreading quickly globally, with major growth in AI job postings and professionals adding AI abilities.
Job postings mentioning AI skills like GPT and ChatGPT have risen dramatically, with a 21x increase since November 2022.
LinkedIn members adding AI skills to profiles is accelerating globally. The number of members with AI skills was 9x larger in June 2023 compared to January 2016.
Singapore, Finland, Ireland, India and Canada have the fastest AI skills adoption rates based on LinkedIn’s AI Skills Index.
47% of US executives believe using generative AI will boost productivity. 40% think it will help drive revenue growth.
84% of US members have jobs that could use AI to automate at least 25% of repetitive tasks. This will also increase demand for people skills.
In the US, the fastest-growing in-demand skills since November 2022 are: Flexibility +158%, Professional ethics +120%, Social perceptiveness +118%, Self-management +83%.
Communication remains the top skill in demand in US job postings, with people skills like flexibility growing the fastest since ChatGPT launched.
92% of executives agree people skills are more important than ever in an AI-driven world.
Why It Matters: AI is transforming and disrupting every industry for sure, but it will never disrupt humanity. Human skills (also called soft skills) like creativity and emotional intelligence will only become more important.
YouTube and Universal Music Partner to Launch ‘AI Incubator’
YouTube is partnering with Universal Music to launch an incubator focused on exploring the use of AI in music. The incubator will work with artists and musicians, including Anitta, ABBA’s Björn Ulvaeus, and Max Ricther, to gather insights on generative AI experiments and research. YouTube CEO Neal Mohan stated that the incubator will inform the company’s approach as it collaborates with innovative artists, songwriters, and producers.
YouTube also plans to invest in AI-powered technology, including enhancing its copyright management tool, Content ID, to protect viewers and creators.
Why does this matter?
By partnering with renowned artists, the AI incubator explores the potential of AI-generated music, spotlighting the intersection of technology and artistry. This collab not only underscores AI’s growing role in creative industries but also demonstrates how industry giants can collaborate to drive innovation and shape the future of music production.
In the ever-evolving landscape of artificial intelligence, Large Language models (LLMs) like GPT-3/GPT-4/Claude-2 and others have exhibited astonishing capabilities across various domains, from mathematical problem-solving to creative writing. However, there’s been a limitation in their approach – the left-to-right, token-by-token decision-making process, which doesn’t always align with complex problem-solving scenarios that demand strategic planning and exploration.
But what if we could enable these LLMs to think more strategically, explore multiple reasoning paths, and evaluate the quality of their thoughts in a deliberate manner? Some researchers have created a framework called “Tree of Thoughts” (ToT) which aims to fix this by enhancing the problem-solving prowess of large language models.
The Essence of ToT
At its core, ToT reimagines the reasoning process as an intricate tree structure. Each branch of this tree represents an intermediate “thought” or a coherent chunk of text that serves as a crucial step toward reaching a solution. Think of it as a roadmap where each stop is a meaningful milestone in the journey towards problem resolution. For instance, in mathematical problem-solving, these thoughts could correspond to equations or strategies.
But ToT doesn’t stop there. It actively encourages the LM to generate multiple possible thoughts at each juncture, rather than sticking to a single sequential thought generation process, as seen in traditional chain-of-thought prompting. This flexibility allows the model to explore diverse reasoning paths and consider various options simultaneously.
Source: Yao et el. (2023)
The Power of Self-Evaluation
One of ToT’s defining features is the model’s ability to evaluate its own thoughts. It’s like having an inbuilt compass to assess the validity or likelihood of success for each thought. This self-evaluation provides a heuristic, a kind of mental scorecard, to guide the LM through its decision-making process. It helps the model distinguish between promising paths and those that may lead to dead ends.
Systematic Exploration
ToT takes strategic thinking up a notch by employing classic search algorithms such as breadth-first search or depth-first search to systematically explore the tree of thoughts. These algorithms allow the model to look ahead, backtrack when necessary, and branch out to consider different possibilities. It’s akin to a chess player contemplating multiple moves ahead before making a move.
Customizable and Adaptable
One of ToT’s strengths is its modularity. Every component, from thought representation to generation, evaluation, and search algorithm, can be customized to fit the specific problem at hand. No additional model training is needed, making it highly adaptable to various tasks.
Real-World Applications
The true litmus test for any AI framework is its practical applications. ToT has been put to the test across different challenges, including the Game of 24, Creative Writing, and Mini Crosswords. In each case, ToT significantly boosted the problem-solving capabilities of LLMs over standard prompting methods. For instance, in the Game of 24, success rates soared from a mere 4% with chain-of-thought prompting to an impressive 74% with ToT.
Source: Yao et el. (2023)
The above image is a visual representation of the Game of 24 which is a mathematical reasoning challenge where the goal is to use 4 input numbers and arithmetic operations to reach the target number 24.
The tree of thought (ToT) approach represents this as a search over possible intermediate equation “thoughts” that progressively simplify towards the final solution.
First, the language model proposes candidate thoughts that manipulate the inputs (e.g. (10 – 4)).
Next, it evaluates the promise of reaching 24 from each partial equation by estimating how close the current result is. Thoughts evaluated as impossible are pruned.
The process repeats, generating new thoughts conditioned on the remaining options, evaluating them, and pruning. This iterative search through the space of possible equations allows systematic reasoning.
For example, the model might first try (10 – 4), then build on this by proposing (6 x 13 – 9) which gets closer to 24. After several rounds of generation and evaluation, it finally produces a complete solution path like: (10 – 4) x (13 – 9) = 24.
By deliberating over multiple possible chains of reasoning, ToT allows more structured problem solving compared to solely prompting for the end solution.
Trained AI algorithms work by taking the input and providing the output without explaining its inner workings. XAI aims at pointing out the rationale behind any decision by AI in such a way that humans can interpret it.
Deep learning works with neural networks just like the human brain works with neurons, where it uses a massive amount of training data to learn and identify patterns. It would be very difficult, or rather impossible, to dig into the rationale behind Deep Learning’s decision. Decisions like credit card eligibility or loan sanction are quite important to be explained by XAI. However, a few wrong decisions would not impact much. Whereas, in the case of healthcare, as discussed earlier, a doctor could not provide the appropriate treatment without knowing the rationale behind AI’s decision. Surgery on the wrong organ could be fatal.
4 Principles of Explainable AI
The US National Institute of Standards and Technology has developed four principles as guidelines to adopt fundamental properties of Explainable Artificial Intelligence (XAI) efficiently and effectively. These principles apply individually and independently from each other and guide us to better understand the working of the AI models.
1. Explanation:
This principle obligates the AI to generate a comprehensive explanation for humans to understand the process of generating the decisions with the required evidence and reasons. The standard for this evidence and reasons is governed by the next three principles.
2. Meaningful:
This principle is satisfied when a stakeholder understands the explanation provided in the first guiding principle. The explanation should not be complex and understood by the users on a group as well as individual level.
3. Explanation Accuracy:
The accuracy at which the AI explains the complicated process of generating the output is critical. Accuracy metrics may differ for individual stakeholders in terms of their explanation. The expected accuracy is 100% for all the stakeholders to understand the logic.
4. Knowledge Limits:
The last principle of XAI explains that the model can only be operated under the special conditions it has been modeled for. It is expected to operate under its limited knowledge to avoid any sort of discrepancy or unjustified business outcomes.
How does XAI work?
These principles help us define the expected output from the XAI model and how an ideal XAI model should be. However, it doesn’t indicate how the output has been achieved. Subdividing the XAI into three categories to better understand the rationale:
1. Explainable data: What data is used to train the model? Why the particular data is selected? How much biased is the data?
2. Explainable predictions: What features did the model use that lead to the particular output?
3. Explainable algorithms: How is the model layered? How do these layers lead to the prediction?
Based on individual instances, the explainability may change. For example, the neural network can only be explained using the Expainable Data category. Research is ongoing that is focused on finding ways to explain the predictions and algorithms. At present there are two approaches:
a. Proxy Modeling:
A different model from the original is used to approximate the actual model. This may result in different outcomes from the true model outcomes, as it is just an approximation.
b. Design for Interpretability:
The actual model is designed in such a way that it is easy to understand its working. However, this increases the risk of reduced predictive power and overall accuracy of the model.
The XAI is referred to as the White Box, as it explains the rationale behind its working. However, unlike the black box, its accuracy may decrease in order to provide an explainable reason for its outcome. Decision trees, Bayesian networks, sparse linear models, and many more are used as explainable techniques. Hopefully, with the advancements in the field, new studies will come up to increase the accuracy of the explanations.
Critical Industries for XAI
XAI would be helpful in those industries where machines play a key part in decision-making. These use cases might also be useful in your industry, as the details may vary, but the core principles remain the same.
1. Healthcare in XAI
As discussed earlier, the decisions made by AI in healthcare impact humans in a very critical way. A machine with XAI would help the healthcare staff save a lot of time, which they might use to focus on treating and attending to more patients. For example, diagnosing a cancerous area and explaining the reason in a matter of time helps the doctor to provide appropriate treatment.
2. Manufacturing in XAI
In the manufacturing industry, fixing or repairing equipment often depends on personnel expertise, which may vary. To ensure a consistent repair process, XAI can help provide ways to repair a machine type with an explanation, record the feedback from the worker, and continuously learn to find the best process to be followed. The workers need to trust the decision made by the machine in order to risk working on the equipment repair, which is the reason XAI becomes useful.
3. Autonomous vehicles in XAI
A self-driving car seems great until and unless it has made a bad decision, which can be deadly. If an autonomous car faces an inevitable accident scenario, the decision it makes impacts greatly on its future use, whether it saves the driver or the pedestrians. Providing the rationale for each decision an autonomous car takes, helps to improve people’s security on the road.
Strategize Your Social Media Campaigns with ChatGPT
Try the propmpt below:
You are a social media strategist. I am launching a crowdfunding campaign for an innovative portable solar charger and need to create a buzz on social media. I need a comprehensive social media strategy that covers platform selection, content ideas, posting frequency, engagement tactics, and analytics tracking. Please provide suggestions considering the latest trends in social media marketing and the behavior of tech-savvy, environmentally-conscious consumers.
YouTube will pay artists and rights holders for AI-generated music used on the platform. This aims to balance creative innovation and fair compensation.
Unraveling August 2023: Spotlight on Generative AI, Tech, Sports and the Month’s Hottest Trends.
Welcome to the hub of the most intriguing and newsworthy trends of August 2023! In this era of rapid development, we know it’s hard to keep up with the ever-changing world of ai, technology, sports, entertainment, and global events. That’s why we’ve curated this one-stop blog post to provide a comprehensive overview of what’s making headlines and shaping conversations. From the mind-bending advancements in artificial intelligence to captivating news from the world of sports and entertainment, we’ll guide you through the highlights of the month. So sit back, get comfortable, and join us as we dive into the core of August 2023!
OpenCopilot allows you to have your own product’s AI copilot. With a few simple steps, it takes less than 5 minutes to build.
It integrates with your underlying APIs and can execute API calls whenever needed. It uses LLMs to determine if the user’s request requires calling an API endpoint. Then, it decides which endpoint to call and passes the appropriate payload based on the given API definition.
Why does this matter?
Shopify has an AI-powered sidekick, while Microsoft (Windows Copilot, Bing Copilot) and GitHub (GitHub Copilot) have copilots. The above innovation empowers every SaaS product to have its own AI copilots tailored for its unique products.
Google teaches LLMs to personalize
LLMs are already good at synthesizing text, but personalized text generation can unlock even more. New Google research has proposed an approach inspired by the practice of writing education for personalized text generation using LLMs. It has a multistage and multitask framework consisting of multiple stages: retrieval, ranking, summarization, synthesis, and generation.
In addition, they introduce a multitask setting that further helps the model improve its generation ability, which is inspired by the observation that a student’s reading proficiency and writing ability are often correlated. When evaluated on three public datasets, each covering a different and representative domain, the results showed significant improvements over various baselines.
Why does this matter?
Customizing style is essential for many domains like personal communication, dialogue, marketing copies, stories, etc., which is hard to do via pure prompt engineering or custom instructions. The research attempts to address this and highlights how we can take inspiration from how humans achieve tasks to apply it to LLMs.
Local Llama
For businesses, local LLMs offer competitive performance, cost reduction, dependability, and flexibility. This article by ScaleDown provides practical guidance on setting up and running LLMs locally using a user-friendly project.
Moreover, Llama-2 and its variants are the go-to models, and the community continually refines them. The article highlights some things to note when running Llama models locally, including memory and model loader challenges.
Why does this matter?
This helps make AI accessible to individuals and businesses while avoiding limitations and high expenses associated with commercial APIs. Locally deploying LLM also helps businesses have more over the model, customize it, integrate with existing systems, and enable full utilization of its capabilities.
AI creates lifelike 3D experiences from your phone video
Luma AI has introduced Flythroughs, an app that allows one-touch generation of photorealistic, cinematic 3D videos that look like professional drone captures. Record like you’re showing the place to a friend, and hit Generate– all on your iPhone. No need for drones, lidar, expensive real estate cameras, and a crew.
Flythroughs is built on Luma’s breakthrough NeRF and 3D generative AI and a brand new path generation model that automatically creates smooth dramatic camera moves.
Why does this matter?
This marks a significant leap in democratizing 3D content creation with AI and making it cost-efficient. It opens up new possibilities for storytelling and crafting stunning digital experiences for users across various industries.
Genetic Algorithm Optimized Neural Network Model for Malicious URL Detection
URL Genie is a web application implementing a Multilayer Perceptron Neural Network optimized using genetic algorithms. Detect whether a domain name or URL is malicious by inputting a URL.
– Boosted.ai – AI stock screening, portfolio management, risk management
– JENOVA – AI stock valuation model that uses fundamental analysis to calculate intrinsic value
– Danielfin – Rates stocks and ETFs with an easy-to-understand global AI Score
– Comparables.ai – AI designed to find comparables for market analysis quickly and intelligently
Daily AI Update News from OpenCopilot, Google, Luma AI, AI2, and more
AI Copilot for your own SaaS product – OpenCopilot allows you to have your own product’s AI copilot. It integrates with your underlying APIs and can execute API calls whenever needed. It uses LLMs to determine if the user’s request requires calling an API endpoint. Then, it decides which endpoint to call and passes the appropriate payload based on the given API definition.
Teach LLMs to Personalize – New Google research has proposed a general approach for personalized text generation using LLMs, inspired by the practice of writing education. Upon evaluation, the results showed significant improvements over a variety of baselines.
Introducing Flythroughs, an app that creates lifelike 3D experiences from your phone video – It allows one-touch generation of photorealistic, cinematic videos that look like professional drone captures. No need for drones, lidar, expensive real estate cameras, and a crew. Record like you’re showing the place to a friend, and hit Generate; all on your iPhone.
Big brands are increasingly using AI-generated ads, including Nestlé and Mondelez – More brands see generative AI as a means to make creating an ad less painful and costly. However, there are concerns over whether to let people know it’s AI-generated, whether AI ads can receive copyright protections, and security risks when using AI.
AI2 drops the biggest open dataset yet for training language models – Language models like GPT-4 and Claude are powerful and useful. Still, the data on which they are trained is a closely guarded secret. The AI2’s (Allen Institute for AI) new, huge text dataset, Dolma, is free to use and open to inspection.
Ex-Machine Zone CEO launches BeFake, an AI-based social media app – Alias Technologies has introduced BeFake, a social media app for digital self-expression. Now available on both the App Store and Google Play, it aims to offer a refreshing alternative to the conventional reality portrayed on existing social media platforms.
Some of the world’s biggest advertisers, from food giant Nestle to consumer goods multinational Unilever, are experimenting with using generative AI software like ChatGPT and DALL-E to cut costs and increase productivity.
The New York Times may sue OpenAI over its AI chatbot ChatGPT, which uses the newspaper’s stories to generate text. The paper is unhappy that OpenAI is not paying for the use of its content and is also worried that ChatGPT could reduce its online traffic by providing answers based on its reporting.
Mantella allows you to have natural conversations with NPCs in Skyrim using your voice by leveraging Whisper for speech-to-text, ChatGPT for text generation, and xVASynth for text-to-speech. NPCs also have memories of your previous conversations and have awareness of in-game events.
British Prime Minister Rishi Sunak is set to spend 100 million pounds ($130 million) to buy thousands of computer chips to power artificial intelligence amid a global shortage and race for computing power.
Imagine a world where you reside in a luxurious home, an architectural marvel adorned with every comfort and amenity that one could possibly fathom. But it doesn’t stop there; your creativity knows no bounds, and you envision entire universes with their own laws of physics, teeming with diverse civilizations.
As you journey through life, your passions take an intriguing turn, guiding you towards the realm of digital marketing.
Yet, amid this shift in interests, a captivating question continues to linger in your mind like an enigmatic riddle: “If I possessed the power to design anything in the world, what wondrous creation would spring forth from my imagination?”
As your knowledge expands and your expertise in digital marketing deepens, you become acquainted with the remarkable world of graphic design software. Herein lies the key to unlock the gateway to your wildest ideas and aspirations.
With the vast array of possibilities that graphic design software offers, you come to realize that you can bring to life virtually anything your mind can conceive – and that realization holds true for anyone daring enough to venture into this realm.
While some graphic design software tools are tailored to cater to specialized fields, such as web design software that masters the dynamic nature of webpages or CAD software that focuses on technical drawings, at its core, graphic design software is an all-encompassing and versatile tool. It empowers individuals to transform their creative visions into tangible realities.
Within the confines of this article, we shall embark on a journey exploring the finest AI design software tools currently available. These cutting-edge tools are poised to revolutionize the design process and elevate your artistic capabilities to unprecedented heights.
By leveraging the power of artificial intelligence, these tools open up new horizons, enabling you to streamline and automate your design workflow like never before.
So, fasten your seatbelts and prepare to delve into the realm of limitless creativity. In the following sections, we shall uncover the potentials of AI-driven design software and how they stand as testaments to the boundless human imagination.
It’s time to manifest your artistic dreams into reality – let the voyage commence!
When it comes to harnessing the power of AI for creating mesmerizing visual graphics, few tools can rival the prowess of Adobe Photoshop CC. Renowned across the globe, this software stands as a beacon of creativity and innovation, empowering artists, designers, and digital enthusiasts to bring their imaginations to life in the most astonishing ways.
At the heart of Adobe Photoshop CC lies an impressive array of features that cater to every aspect of design. Whether you aim to craft captivating illustrations, design stunning artworks, or manipulate photographs with unprecedented precision, this software has got you covered.
With its user-friendly interface and intuitive controls, even those new to the world of digital design can quickly find themselves delving into the realm of endless possibilities.
One of the standout strengths of Photoshop lies in its ability to produce highly realistic and detailed images. From refining minute details in portraits to creating breathtaking landscapes, the software’s tools and filters enable artists to achieve a level of precision that defies belief.
The result is a visual masterpiece that captures the essence of the creator’s vision with unparalleled fidelity.
But Photoshop is not merely limited to polishing existing images; it opens the gates to boundless creativity by allowing users to remix and combine multiple images seamlessly. Whether it’s composing fantastical scenes or crafting surreal montages, the software’s blending capabilities grant designers the freedom to construct their own visual universes.
What truly sets Adobe Photoshop CC apart from the rest is its ingenious integration of artificial intelligence. The inclusion of AI-driven features elevates the design process to a whole new dimension.
Dull and lackluster photographs transform into jaw-dropping works of art with just a few clicks, as the software’s AI algorithms intelligently enhance colors, textures, and lighting, breathing life into every pixel.
Adobe’s suite of creative tools, including the likes of Adobe Illustrator and others, work in seamless harmony with Photoshop. This synergy empowers designers to amplify their creative potential even further.
Whether you’re crafting a logo, designing a website, or creating intricate vector graphics, the integration of these tools allows you to transcend the boundaries of imagination.
Planner 5D stands as an ingenious AI-powered solution, offering you the gateway to realize your long-cherished dream of a perfect home or office space. With its cutting-edge technology, this software empowers you to dive into the realm of architectural creativity and interior design like never before.
The first remarkable feature that sets Planner 5D apart is its AI-assisted design capabilities. Imagine describing your ideal home or office, and watch as the AI effortlessly translates your vision into a stunning 3D representation. From grand entrances to cozy corners, the AI understands your preferences, ensuring that every aspect of your dream space aligns with your desires.
Gone are the days of struggling with pen and paper to create floor plans. Planner 5D streamlines the process, enabling you to effortlessly design detailed and precise floor plans for your dream space.
Whether you seek an open-concept layout or a series of interconnected rooms, this software provides the tools to bring your architectural visions to life.
But that’s not all – Planner 5D goes above and beyond to cater to every facet of interior design. With an extensive library of furniture and home décor items at your disposal, you can furnish and decorate your space with ease.
From stylish sofas and elegant dining tables to enchanting wall art and lighting fixtures, the possibilities are limitless.
The user-friendly 2D/3D design tool within Planner 5D is a testament to the software’s commitment to simplicity and innovation. Whether you’re an aspiring designer or a seasoned professional, navigating through the interface is a breeze, allowing you to create the perfect space for yourself, your family, or your business with utmost ease and precision.
For those seeking a more hands-off approach, Planner 5D also offers the option to hire a professional designer through their platform. This feature is a boon for individuals who desire a polished and expertly curated space but prefer to leave the intricate details to the experts.
By collaborating with skilled designers, you can rest assured that your dream home or office will become a reality, tailored to your unique taste and requirements.
Uizard emerges as a game-changing tool that holds the power to transform the creative process for founders and designers alike. This innovative software enables you to breathe life into your ideas by swiftly converting your initial sketches into high-fidelity wireframes and stunning UI designs.
Gone are the days of spending endless hours painstakingly crafting wireframes and prototypes manually. With Uizard, the transformation from a low-fidelity sketch to a polished, high-fidelity wireframe or UI design can occur within mere minutes.
The speed and efficiency afforded by this cutting-edge technology empower you to focus on refining your concepts and iterating through ideas at an unprecedented pace.
Whether your vision encompasses web apps, websites, mobile apps, or any digital platform, Uizard stands as a reliable companion, streamlining the design process with its versatility. You no longer need to possess extensive design expertise, as the tool is intuitively designed to cater to users of all backgrounds and skill levels.
From tech-savvy founders to aspiring entrepreneurs, Uizard ensures that the creative journey remains accessible and enjoyable for everyone.
The user-friendly interface of Uizard opens up a realm of possibilities, allowing you to bring your vision to life with ease. Its intuitive controls and extensive feature set empower you to craft pixel-perfect designs that align with your unique style and brand identity.
Whether you’re a solo founder or part of a dynamic team, Uizard fosters seamless collaboration, enabling you to share and iterate on designs effortlessly.
One of the most significant advantages of Uizard lies in its ability to gather invaluable user feedback on your designs. By sharing your wireframes and UI designs with stakeholders, clients, or potential users, you can gain insights and refine your creations based on real-world perspectives.
This not only accelerates the decision-making process but also ensures that your final product resonates with your target audience.
Enter the extraordinary realm of 3D animation with Autodesk Maya, a software that transcends conventional boundaries to grant you the power to breathe life into expansive worlds and intricate characters. Whether you’re an aspiring animator, a seasoned professional, or a visionary storyteller, Maya provides the tools to transform your creative visions into stunning reality.
Imagination knows no bounds with Maya, as its powerful toolsets empower you to embark on a journey of endless possibilities. From the grandest of cinematic tales to the most whimsical of animated adventures, this software serves as your creative canvas, waiting for your artistic touch to shape it.
Complexity is no match for Maya’s prowess, as it deftly handles characters and environments of any intricacy. Whether you seek to create lifelike characters with nuanced emotions or craft breathtaking landscapes that transcend the boundaries of reality, Maya’s capabilities rise to the occasion, ensuring that your artistic endeavors know no limits.
Designed to cater to professionals across various industries, Maya stands as the perfect companion for crafting high-quality 3D animations for movies, games, and an array of other purposes. Its versatility makes it a go-to choice for animators, game developers, architects, and designers alike, unleashing the potential to tell stories and visualize concepts with stunning visual fidelity.
The heart of Maya lies in its engaging animation toolsets, each one carefully crafted to nurture the growth of your virtual world. From fluid character movements to dynamic environmental effects, Maya opens the doors to your creative sanctuary, enabling you to weave intricate tales that captivate audiences across the globe.
But the journey doesn’t end there – with Autodesk Maya, you are the architect of your digital destiny. As you explore the depths of this software, you discover its seamless integration with other creative tools, expanding your capabilities even further.
The synergy between Maya and its counterparts unlocks new avenues for innovation, granting you the freedom to experiment, iterate, and refine your creations with ease.
Aimed at architects, engineers, and a myriad of other professionals, this cutting-edge tool serves as a gateway to bring your imaginative designs to life with astonishing realism.
Architects find solace in Autodesk 3Ds Max as it empowers them to create stunningly realistic models of their architectural wonders. Engineers, too, discover the power of this software in crafting intricate and precise 3D models of their mechanical and industrial designs.
The software becomes a haven for creative professionals seeking to visualize and communicate their concepts with exceptional clarity and visual fidelity.
Beyond the realms of architecture and engineering, Autodesk 3Ds Max knows no bounds. Its versatility allows you to explore various dimensions of creativity, from crafting intricate product prototypes to fashioning enchanting animated characters.
Whatever your design aspirations may be, this software stands as a reliable companion, ensuring that your visions manifest into awe-inspiring digital realities.
In the fast-paced world of business and design, having a tool that caters to multiple purposes becomes invaluable. Autodesk 3Ds Max stands tall as a versatile and adaptable solution, making it a coveted asset for businesses and individuals alike.
Its potential to enhance the visual storytelling capabilities of any venture unlocks a new era of creativity and communication.
One of the most cherished qualities of Autodesk 3Ds Max lies in its user-friendly interface, fostering a seamless and intuitive design process. With this tool at your disposal, iteration becomes a breeze, allowing you to refine your designs effortlessly.
Each new iteration becomes a steppingstone towards perfection, ensuring that your final creation exudes excellence.
With Foyr Neo at your disposal, you can witness the transformation of your design ideas into reality in as little as a fifth of the time it takes with other software tools.
Gone are the days of grappling with complex design interfaces and spending endless hours on a single project. Foyr Neo streamlines the journey from a floor plan to a finished render, presenting you with a user-friendly interface that simplifies every step of the design process.
With its intuitive controls and seamless functionality, the software becomes an extension of your creative vision, ensuring that your ideas manifest into remarkable designs with utmost ease.
To further elevate your experience, Foyr Neo provides a thriving community and comprehensive training resources. This collaborative ecosystem allows you to connect with fellow designers, share insights, and gain inspiration from the collective creative pool.
Additionally, the abundance of training materials and support ensures that you can unlock the full potential of the software, mastering its capabilities and expanding your design horizons.
Bid farewell to the hassle of juggling multiple tools to complete a single project – Foyr Neo serves as the all-in-one solution to cater to your design needs. By integrating various design functionalities within a single platform, the software streamlines your workflow, saving you precious time and effort.
This seamless experience fosters uninterrupted creativity, enabling you to focus on the art of design without the burden of managing disparate software tools.
With this cutting-edge software, you can witness a remarkable increase in image resolution of up to 16 times, all without sacrificing an ounce of quality.
Gone are the days of tedious manual editing, spending hours painstakingly enhancing your images pixel by pixel. Let’s Enhance simplifies the process, offering a swift and efficient solution to elevate your photos’ quality with ease.
Whether you’re a professional photographer seeking crisper images for print or a social media enthusiast aiming to enlarge your visuals, this software promises to deliver the perfect shot every time.
Let’s Enhance’s proficiency in improving image resolution, colors, and lighting automatically alleviates the burden of post-processing. By entrusting this task to the intelligent algorithms of the software, you gain more time to focus on the core aspects of your business or creative endeavors.
Embrace the art of delegation and allow Let’s Enhance to handle the technicalities while you concentrate on perfecting your artistic vision.
The applications of Let’s Enhance are vast and diverse. Photographers, designers, artists, and marketers alike can benefit from this powerful tool. Imagine effortlessly preparing your images for print, knowing they’ll boast impeccable clarity and sharpness.
Envision your social media posts grabbing attention with larger-than-life visuals, thanks to Let’s Enhance’s seamless enlargement capabilities.
But Let’s Enhance doesn’t stop at resolution enhancement. It also becomes a reliable ally in refining color palettes, breathing new life into dull or faded images, and balancing lighting for picture-perfect results.
Whether it’s subtle adjustments or dramatic transformations, the software empowers you to create visuals that captivate audiences and leave a lasting impression.
6 AI Text to Video compared (updated August 2023 ) Link
Runway Features
– Text-to-video feature – Automatic prompt suggestions – The option to upload an image for reference – Different previews to choose from before generating a video – Free plan to test the tool out
Pros
– Best of AI text-to-video research – Comprehensive set of tools for video editing – Available as both a desktop and mobile app
Cons
– Gen-2 has limitations in generating intricate details, like fingers – Gen-2 video generation is limited to 4 seconds per video – The tool does not offer text-to-speech capabilities
Synthesia AI Features
– 120+ voices and accents – 140+ diverse AI avatars – 60+ video templates designed by professional designers – The option to have a custom avatar created
In today’s world, messaging apps are becoming increasingly popular, with WhatsApp being one of the most widely used. With the help of artificial intelligence, chatbots have become an essential tool for businesses to improve their customer service experience. Chatbot integration with WhatsApp has become a necessity for businesses that want to provide a seamless and efficient customer experience. ChatGPT is one of the popular chatbots that can be integrated with WhatsApp for this purpose. In this blog post, we will discuss how to integrate ChatGPT with WhatsApp and how this chatbot integration with WhatsApp can benefit your business.
The site uses openAI to generate trivia on anything and everything you want ! You can then revisit trivia you or others have made and replay them at anytime.
Solo & real time multiplayer, daily challenge, infinite playability and is getting updates daily !
Current feature roadmap :
jeopardy mode ( multiple topics and large question count )
email / sms notifications for new daily challenges etc.
public lobbies / multiplayer against random players
IBM’s study indicates that 40% of the global workforce, or 1.4 billion people, will need to reskill in the next three years due to AI’s rise.
While AI technologies, such as generative models, might shift job responsibilities, 87% of surveyed executives believe AI will augment jobs rather than replace them.
The focus in job skills has shifted from technical STEM skills (most important in 2016) to people skills like team management and adaptability (most important in 2023).
Meta did it first… Generative AI for producers
Generative AI is revolutionizing this decade’s technology, breaking into the realm of creativity once reserved for humans. Jobs are shifting, with some roles being replaced and others benefiting from AI assistance.
Content creators, take note! Meta just revealed that platforms like Facebook and Instagram will employ AI to produce music. This means no more copyright issues or losing business. Simply choose a genre, provide a sample, and the AI crafts tailor-made music for your videos.
Facebook’s music library becomes obsolete as Meta leads the way, while YouTube and TikTok will likely follow suit. As a content creator, AI eliminates rights concerns. However, creators of original music may face challenges.
AI’s impact extends to various fields, affecting writers, musicians, artists, and photographers. While some might feel the pinch, the creative economy as a whole benefits, making custom content creation easier.
Imagine conceiving, designing, and animating with AI—a reality that even big players like Disney face. This emerging world is thrilling and transformative.
To prepare, embrace AI. Integrate it into your work wherever possible. If you want to stay ahead and not fall behind to AI, leverage its capabilities.
Trustworthy LLMs: A survey and guideline for evaluating LLMs’ alignment
Ensuring alignment, which refers to making models behave in accordance with human intentions, has become a critical task before deploying LLMs in real-world applications. This new research has proposed a more fine-grained taxonomy of LLM alignment requirements. It not only helps practitioners unpack and understand the dimensions of alignments but also provides actionable guidelines for data collection efforts to develop desirable alignment processes.
It also thoroughly surveys the categories of LLMs that are likely to be crucial to improve their trustworthiness and shows how to build evaluation datasets for alignment accordingly.
The tool curates high-quality data that leads to improved LLM downstream performance and will significantly benefit LLM developers attempting to build pretraining datasets.
Microsoft-DataBricks collab may hurt OpenAI
Microsoft is reportedly planning to sell a new version of Databricks software, It helps customers create AI applications for their businesses. This move could potentially harm OpenAI, as Databricks allows companies to develop AI models from scratch or repurpose open-source models instead of licensing OpenAI’s proprietary ones.
Microsoft has been aggressively investing in AI services and integrating AI functionality across its products. Neither Microsoft nor Databricks have commented on the report.
What else happened in AI this week of August 12-20?
Google appears to be readying new AI-powered tools for ChromeOS
Zoom rewrites policies to make clear user videos aren’t used to train AI
Anthropic raises $100M in funding from Korean telco giant SK Telecom
Modular, AI startup challenging Nvidia, discusses funding at $600M valuation
California turns to AI to spot wildfires, feeding on video from 1,000+ cameras
FEC to regulate AI deepfakes in political ads ahead of 2024 election
Google’s AI search offers AI-generated summaries, definitions, and coding improvements.
Google Photos introduce a new AI feature, ‘Memories view’!
Amazon using AI to enhance product reviews.
WhatsApp test beta upgrade with new feature ‘custom AI-generated stickers’.
Google is testing an AI assistant that will give you Life Advice.
Robomart adopts “store-hailing” for self-driving stores delivered to customers.
OpenAI acquires AI design studio Global Illumination to work on core products, ChatGPT
The Associated Press releases guidelines for Generative AI to its journalists
Consulting giant McKinsey unveils its own generative AI tool for employees: Lilli
Opera for iOS will now include Aria, its browser AI built in collaboration with OpenAI
UK is using AI road safety cameras to detect potential driver offenses in passing vehicles
Adobe Express with AI Firefly app, now out of beta, is available worldwide
Ex-Google Brain researchers have started an AI research company called Sakana AI in Tokyo.
Runway, a gen AI video startup, has launched a new ‘Watch’ feature.
Research shows AI bots beat CAPTCHA and humans.
ML startup Arthur launched an open-source tool to help find the best LLM.
Buildbox has launched a new tool called StoryGames.AI!
Latest Tech News and Trends on August 20th, 2023
Major concerns after Cruise robotaxi incidents
Following a recent collision between a Cruise robotaxi and a fire truck in San Francisco, the California DMV requested Cruise to halve its robotaxi fleet in the city.
The state agency is investigating “recent concerning incidents” with Cruise vehicles, emphasizing the need to ensure the safety of the public sharing the road with these autonomous vehicles.
This specific accident saw a Cruise Chevy Bolt EV hit by an emergency vehicle at an intersection, resulting in passenger injuries; it adds to a series of issues potentially affecting Cruise’s future operations.
As wildfires spread, Canadian leaders ask Meta to reverse its news ban
The Canadian government demands that Meta lift its ban on domestic news sharing, citing its impact on sharing information about wildfires.
Meta blocked news on Facebook and Instagram due to a new law requiring payment for news articles, but this move hampers access to crucial information.
Officials and citizens express concerns, urging Meta to reinstate news sharing for safety and emergency information during the wildfire crisis.
X to remove ‘block’ feature
Elon Musk suggests that Twitter’s block feature, except for direct messages, may be removed, causing concern among users.
Blocking is currently used to restrict interactions and visibility of accounts, while mute only hides posts; users value blocking for spam control and harassment prevention.
Musk’s statement prompts backlash and uncertainty about whether the feature will actually be removed.
Discover the OpenAI code interpreter, an AI tool that translates human language into code. Learn about its functions, benefits and drawbacks in this guide.
The basics of OpenAI code interpreter
OpenAI, a leading entity in the field of artificial intelligence, has developed OpenAI code interpreter, a specialized model trained on extensive data sets to process and generate programming code.
OpenAi code interpreter is a tool that attempts to bridge the gap between human language and computer code, offering myriad applications and benefits. It represents a significant step forward in AI capabilities. It is grounded in advanced machine learning techniques, combining the strengths of both unsupervised and supervised learning. The result is a model that can understand complex programming concepts, interpret various coding languages, and generate human-like responses that align with coding practices.
New Generations of People Are Becoming More and More Indistinguishable from AI
One of the most concerning aspects of this trend is the way that new generations are rewriting previous information. In the past, people would typically come up with their ideas and opinions. However, today, it is much more common for people to simply rewrite information that they have found online. This is a trend that is being exacerbated by the rise of large language models (LLMs), which can generate text that is nearly indistinguishable from human-written text. Article: new-generations-of-people-are-becoming-more-and-more-indistinguishable-from-ai/
Neolithics, an agritech company based in Israel, is using artificial intelligence and machine learning to reduce food waste and ensure food safety and quality through its optical sensing AI-powered solution known as Crystal.eye™. This technology, which can be mounted and configured in various ways, automates and upgrades quality control for fresh produce, in order to maximize utilization and reduce waste.
While the normal spectrum of visible light has 3 colors – red, green, and blue, Crystal.eye™ uses hyperspectral imaging, with over 400 spectra of light. This light can penetrate deep into a fruit or vegetable and allows the device to scan even inside the sample, eliminating the need to cut it open or grind it.
The images produce a unique fingerprint, which is then analyzed by Neolithics’ food scientists to identify various characteristics, such as firmness, moisture content, sugar content, acidity, and many more. The data is then fed to an AI machine learning engine, allowing the system to scan and analyze a large batch of samples in a matter of seconds.
The outcomes of the inspections are then instantly displayed on a digital dashboard and can be delivered as reports, tailored to each customer’s unique requirements. For example, french fry makers need to know how much dry matter is contained in the potatoes they process, while winemakers take into account the grapes’ acidity and sweetness to obtain the flavor profile they desire.
Using Crystal.eye™ allows growers and distributors to greatly expand their sampling, from the usual 1% to around 30% to 40%. This ensures greater accuracy and significantly reduces the chance of produce being discarded due to not meeting the customers’ requirements.
According to Wayne Nathanson, the company’s VP for Global Development, knowledge in food science is Neolithics’ main differentiator. While there are other companies that make the hardware to move around and sort fruits and vegetables, he says that usually these technologies work on exterior qualities, and aren’t able to analyze the produce’s interior. Most companies do not have a team of expert food scientists to fully harness the information gathered from the produce like Neolithics, he adds.
Currently, Crystal.eye™ can check the content or defects of produce, providing customers with various external or internal attributes. This solution has been launched and is being used by an increasing number of growers, distributors, and food processing companies. At the end of this year, Neolithics expects to update the technology with the capability to assess the produce’s maturity cycle, allowing customers to identify how long it will take before it spoils. The company is also working on being able to identify traces of pesticides and other banned chemicals on the produce, with release estimated for next year.
“Sustainability is very important to Neolithics, and our mission is to reduce food waste and improve food safety. Knowing how much food is wasted daily is a major motivator for making a difference. We want to eliminate food wastage across the supply chain, including removing the need to destroy the produce when it’s being inspected. We also want to get more edible quality produce to the consumer, by helping the various links of the supply chain distribute it better. There are 1.3 billion tons of wasted food annually, and there are roughly a billion people in the world experiencing hunger. We believe there’s an opportunity to feed more people with the food that is thrown out. This becomes more and more critical, the closer the world population gets to the 10 billion mark,” Nathanson says.
The new AI programming jobs that require only very basic programming skills
There has never been a more exciting and promising time to get into AI development. Forbes reports that job listings for ChatGPT-related positions increased 21 times since last November:
They need both prompt engineers and programmers. But because of Copilot and other advances in AI programming they are looking for people with some basic programming skills but who mainly excel in advanced critical analysis and reasoning skills.
They basically need people who know how to think so for people with IQs above 130, (in the genius range) this could be a dream career. But really it’s not so much about IQ as it is about the ability to think rather than just mostly learn and remember. In fact programming courses must already be teaching this brand new kind of prompt engineering and programming.
I imagine that computer programming instruction is going through very rapid evolution right now as teaching fundamental programming skills more and more gives way to teaching how to most quickly and intelligently prompt AIs to do whatever programming is needed.
If incumbent programming schools are not changing fast enough they risk losing a substantial market share to startups that begin teaching much more marketable skills.
Many businesses today want to start using AIs but they don’t know how to go about it. Computer programmers and prompt engineers who can explain all of this to them have a ready and rapidly growing job market.
Yeah there could never be a better time to get into computer programming!
The importance of making superintelligent small LLMs
Google’s Gemini will set a new standard in AI largely because of the massive data set that it is trained on.
If you’re not familiar with Gemini yet, watch this amazingly intelligent 8-minute YouTube video:
The next step would be for Google to train that stronger intelligence to shift from relying on data to relying on principles for its logic and reasoning.
Once AI’s intelligence is based on principles, subsequent iterations will no longer require massive data for their training.
That achievement will level the playing field so that Gemini is much sooner joined by competitive or stronger models.
Once that happens, everything will get very intelligent.
As Hollywood strikes, 96% of entertainment companies are boosting generative AI spend
As the Hollywood strike continues, 96% of entertainment companies are ramping up their investments in generative AI, revealing a shift in the industry’s approach to content creation and potential concerns for its workforce.
If you want to stay ahead of the curve in AI and tech, look here first.
The rise in AI spending amidst the Hollywood strike
The Hollywood writer’s strike underscores a shift in the entertainment industry’s investment strategy.
Lucidworks’ research, one of the largest of its kind, shows 96% of executives prioritize generative AI investments.
Countries like China, the UK, France, India, and the U.S. have companies heavily investing in this technology.
AI’s potential impact on Hollywood content creation
Generative AI can produce content, virtual environments, and images, posing a potential disruption to traditional methods.
Predictions suggest that by 2025, up to 90% of Hollywood content could be influenced by AI.
There’s a growing concern among Hollywood writers about the rapid integration of AI and its effect on their careers.
The future of the entertainment industry with generative AI
The emergence of synthetic actors could revolutionize the way movies and shows are produced.
AI-driven actors don’t strike, age, or demand pay raises, presenting potential benefits for studios but challenges for human actors.
Microsoft is reportedly planning to sell a new version of Databricks software, It helps customers create AI applications for their businesses. This move could potentially harm OpenAI, as Databricks allows companies to develop AI models from scratch or repurpose open-source models instead of licensing OpenAI’s proprietary ones.
Microsoft has been aggressively investing in AI services and integrating AI functionality across its products. Neither Microsoft nor Databricks have commented on the report.
Why does this matter?
Microsoft’s reported intention to introduce an AI-focused Databricks software version carries implications for OpenAI. This software empowers businesses to craft AI solutions without relying on OpenAI’s proprietary models, potentially impacting OpenAI’s market.
Meta AI’s new RoboAgent with 12 skills
Meta and CMU Robotics Institute’s New Robotics research: RoboAgent. It is a universal robotic agent that can efficiently learn and generalize a wide range of non-trivial manipulation skills. It can perform 12 skills across 38 tasks, including object manipulation and re-orientation, and adapt to unseen scenarios involving different objects and environments.
The development of the RoboAgent was made possible through a distributed robotics infrastructure, a unified framework for robot learning, and a high-quality dataset. The agent also utilizes a language-conditioned multi-task imitation learning framework to enhance its capabilities. Meta is open-sourcing RoboSet, a large, high-quality robotics dataset collected with commodity hardware, to support and accelerate open-source research in robot learning.
Why does this matter?
RoboAgent has the potential to accelerate automation, manufacturing, and daily tasks as the end users can enjoy more capable and helpful robots at home. Industries can streamline operations with efficient automation, technology could push AI and robotics boundaries, and innovation might surge across sectors.
Meta challenges OpenAI with code-gen free software
Meta is set to release Code Llama, an open-source code-generating AI model that competes with OpenAI’s Codex. The software builds on Meta’s Llama 2 model and allows developers to automatically generate programming code and develop AI assistants that suggest code.
Llama 2 disrupted the AI industry by enabling companies to create AI apps without relying on proprietary software from major players like OpenAI, Google, or Microsoft. Code Llama is expected to launch next week, further challenging the dominance of existing code-generating AI models in the market.
Why does this matter?
Meta’s Code Llama is set to rival OpenAI’s Codex; this open-source AI model is an update of Meta’s Llama 2. This tool challenges giants like OpenAI, Google, and Microsoft, giving developers more control and reducing dependence on their proprietary tools.
AP sets new AI guidelines for newsrooms
The Associated Press has established standards for the use of generative AI in its newsroom, emphasizing that AI is not a replacement for human journalists and cautioning against creating publishable content with AI-generated text or images.
AP journalists are directed to treat AI-generated content as “unvetted source material” and apply editorial judgment and sourcing standards before considering it for publication.
The organization warns about the potential for AI to spread misinformation and advises its journalists to exercise caution, skepticism, and verify sources when dealing with AI-generated content.
Latest Tech News and Trends on August 18th, 2023
Scientists are leaving X
A significant portion of scientific researchers using X have reduced their usage or left the platform altogether, with over 47% decreasing usage and nearly 7% quitting, according to a survey by Nature.
About 47% of polled researchers have turned to alternative platforms, with Mastodon being the most popular, followed by LinkedIn and Instagram.
The change in researcher behavior on X is attributed to the platform’s evolving dynamics, increased content prioritization, and limited accessibility of its API for researchers.
Amazon imposes fees on self-shipping sellers
Starting from October 1st, third-party merchants on Amazon who ship their own packages will be required to pay a 2% fee per product sold.
This new fee is in addition to other charges Amazon already receives from merchants, including selling plan costs and referral fees based on product categories.
The fee comes as Amazon’s marketplace is under scrutiny, with the FTC planning to file an antitrust lawsuit over allegations that Amazon rewards third-party merchants using its logistics services while penalizing those fulfilling their own orders.
NYC bans TikTok from government devices
New York City is banning TikTok from government devices within 30 days, with immediate prohibition on downloading and usage by employees.
The NYC Cyber Command cited TikTok as a security threat to the city’s technical networks, prompting the decision.
While some states have broadly banned TikTok, most have restricted its use on government-owned tech, amid ongoing debates about the app’s security risks.
Unraveling August 2023: August 17th, 2023
Latest AI News and Trends on August 17th, 2023
You can now write one sentence to train an entire ML model.
How does it work?
You just describe the ML model you want…a chain of AI systems will take that sentence…it generates a dataset based on that sentence…and it trains a model for you…in ten minutes 😳
What does that mean?
Custom models in AI just got a whole lot easier. You can go from an idea (“a model that writes Python functions”) to a fully trained custom Llama-2 model in minutes 😮
Why should I care?
If you aren’t thinking about the impact of change in your industry, start now. It’s not linear and continuous, it’s exponential with step functions. 3 out of 4 C-suite executives believe that if they don’t scale artificial intelligence in the next five years, they risk going out of business entirely.
What should I do about it?
Further proof that AI is changing our work processes rapidly. You need to build a team and org that’s first and foremost, ready for change. And if you haven’t started pulling together an AI working group to get cracking on your AI usage principles and first AI use case, do it.
GPT-4 Code Interpreter masters math with self-verification
OpenAI’s GPT-4 Code Interpreter has shown remarkable performance on challenging math datasets. This is largely attributed to its step-by-step code generation and dynamic solution refinement based on code execution outcomes.
Expanding on this understanding, new research has introduced the innovative explicit code-based self-verification (CSV) prompt, which leverages GPT4-Code’s advanced code generation mechanism. This prompt guides the model to verify the answer and then reevaluate its solution with code.
The approach achieves an impressive accuracy of 84.32% on the MATH dataset, significantly outperforming the base GPT4-Code and previous state-of-the-art methods.
Why does this matter?
The study provides the first systematic analysis of the role of code generation, execution, and self-debugging in mathematical problem-solving. This highlights the importance of code understanding and generation capabilities in LLMs. Plus, the ideas presented can help build high-quality datasets that could potentially help improve the mathematical capabilities in open-source LLMs like Llama-2.
Multi-level machine learning models for estimating the risk of delay between cancer diagnosis and treatment initiation in a large group of cancer patients.
Study significance
Machine learning models that incorporate multi-level data sources can effectively identify cancer patients who are at a greater risk of experiencing treatment delays of more than 60 days after their initial cancer diagnosis.
Although neighborhood-level social determinants of health are incorporated in the study model as contributing variables, no significant impact of these factors was observed on the model performance. Furthermore, the model exhibits lower predictive effectiveness in vulnerable populations.
Future studies should include a higher proportion of vulnerable populations and more relevant social variables to improve the model performance.
Journal reference:
Frosch Z. A. K., Hasler, J., Handorf, E., et al. (2023). Development of a Multilevel Model to Identify Patients at Risk for Delay in Starting Cancer Treatment. JAMA Network Open. doi:10.1001/jamanetworkopen.2023.28712, https://jamanetwork.com/journals/jamanetworkopen/fullarticle/2808249
Discover the top AI jobs shaping the future. Navigate the booming AI industry with insights on rewarding careers.
1. AI product manager
An AI product manager is similar to other program managers. Both jobs require a team leader to develop and launch a product. In this case, it is an AI product, but it’s not much different from any other product in terms of leading teams, scheduling and meeting milestones.
AI product managers need to know what goes into making an AI application, including the hardware, programming languages, data sets and algorithms, so that they can make it available to their team. Creating an AI app is not the same as creating a web app. There are differences in the structure of the app and the development process.
2. AI research scientist
An AI research scientist is a computer scientist who studies and develops new AI algorithms and techniques. They develop and test new AI models, collaborate with other researchers, publish research papers and speak at conferences. So, programming is only a small portion of what a research scientist does.
The tech industry is extremely open to self-taught and non-formally trained programmers, but it makes an exception for AI research scientists. They need to have a strong understanding of computer science, mathematics and statistics. Typically, they need graduate degrees.
3. Big data engineer
AI works with large data sets and so does its precursor, big data. A big data engineer is similar to an AI engineer because they are responsible for designing, building, testing and maintaining complex data processing systems that work with large data sets. But, instead of working with GPT or LaMDA, they work with big data tools, like Hadoop, Hive, Spark and Kafka.
Like AI researchers, big data engineers often have advanced degrees in mathematics and statistics. These degrees are necessary for designing, maintaining and building data pipelines based on massive data sets.
Business intelligence (BI) is also a data-driven discipline that predates the modern AI rush. Like big data and AI, BI also relies on large data sets. BI developers use data analytics platforms, reporting tools and visualization techniques to turn raw data into meaningful insights to help organizations make informed decisions.
BI developers work with a variety of coding languages and tools from major vendors, including SQL, Python, Tableau from Salesforce and Power BI from Microsoft. They also need to have a strong understanding of business processes to help improve them through data insight.
5. Computer vision engineer
A computer vision engineer is a developer who specializes in writing programs that utilize visual input sensors, algorithms and systems. These systems see the world around them and act accordingly, such as self-driving and self-parking cars and facial recognition.
They use languages like C++ and Python, along with visual sensors, such as Mobileye from Intel. Examples of use cases include object detection, image segmentation, facial recognition, gesture recognition and scenery understanding.
6. Data scientist
A data scientist is a technology professional who collects, analyzes and interprets data to solve problems and drive decision-making within the organization. They are not necessarily programmers, although many do write their own applications. Mostly, they use data mining, big data and analytical tools.
Their use of business insights derived from data enables businesses to improve sales and operations; make better decisions; and develop new products, services and policies. They use predictive modeling to forecast future events, such as customer churn, and data visualization to display research results visually. Some also use machine learning to build models to automate these tasks.
7. Machine learning engineer
A machine learning engineer is responsible for developing and implementing machine learning training algorithms and models. Training is the demanding side of machine learning and is the most processor- and computation-intensive aspect of machine learning. Therefore, it requires the highest level of skill and training.
Because of the need for advanced math and statistics skills, most machine learning engineers have advanced degrees in computer science, math or statistics. They often continue training through certification programs or a master’s degree in machine learning, deep learning or neural networks.
8. Natural language processing engineer
A natural language processing (NLP) engineer is a computer scientist who specializes in the development of algorithms and systems that understand and process natural human language input.
One of the big differentiators between traditional search engines and generative AI interfaces, such as ChatGPT, is that search engines use keywords and gather information from large amounts of existing online data. Generative AI creates new content based on other examples and patterns, and it answers queries in a chat-type format.
Like machine learning engineers, NLP engineers are not necessarily programmers first. They need to understand linguistics as much as they need to understand programming. NLP projects require machine translation, text summarization, answering questions and understanding context.
9. Robotics engineer
A robotics engineer is a developer who designs, develops and tests software for running and operating robots. Robotics has advanced significantly in recent years, such as automated home cleaners and precision cancer surgery equipment. Robotics engineers may also use AI and machine learning to boost a robotic system’s performance.
As a result, robotics engineers are typically designing software that receives little to no human input but instead relies on sensory input. Therefore, a robotics engineer needs to debug the software and the hardware to make sure everything is functioning as it should.
Robotics engineers typically have degrees in engineering, such as electrical, electronic or mechanical engineering.
10. Software engineer
A software engineer can cover various activities in the software development chain, including design, development, testing and deployment. Engineering professionals are needed at all points of software development. The demands are so high that it’s rare to find someone well versed in all of them. Most engineers tend to specialize in one discipline.
We spoke with MIT CSAIL head Daniela Rus about the emerging technology of liquid networks and implications for robotics.
The initial research papers date back to 2018, but for most, the notion of liquid networks (or liquid neural networks) is a new one. It was “Liquid Time-constant Networks,” published at the tail end of 2020, that put the work on other researchers’ radar. In the intervening time, the paper’s authors have presented the work to a wider audience through a series of lectures.
Ramin Hasani’s TEDx talk at MIT is one of the best examples. Hasani is the Principal AI and Machine Learning Scientist at the Vanguard Group and a Research Affiliate at CSAIL MIT, and served as the paper’s lead author.
“These are neural networks that can stay adaptable, even after training,” Hasani says in the video, which appeared online in January. When you train these neural networks, they can still adapt themselves based on the incoming inputs that they receive.”
The “liquid” bit is a reference to the flexibility/adaptability. That’s a big piece of this. Another big difference is size. “Everyone talks about scaling up their network,” Hasani notes. “We want to scale down, to have fewer but richer nodes.” MIT says, for example, that a team was able to drive a car through a combination of a perception module and liquid neural networks comprised of a mere 19 nodes, down from “noisier” networks that can, say, have 100,000.
“A differential equation describes each node of that system,” the school explained last year. “With the closed-form solution, if you replace it inside this network, it would give you the exact behavior, as it’s a good approximation of the actual dynamics of the system. They can thus solve the problem with an even lower number of neurons, which means it would be faster and less computationally expensive.”
The concept first crossed my radar by way of its potential applications in the robotics world. In fact, robotics make a small cameo in that paper when discussing potential real-world use. “Accordingly,” it notes, “a natural application domain would be the control of robots in continuous-time observation and action spaces where causal structures such as LTCs [Liquid Time-Constant Networks] can help improve reasoning.”
AI reconstructs song from brain activity
Neuroscientists recorded electrical activity from areas of the brain (yellow and red dots) as patients listened to the Pink Floyd song “Another Brick in the Wall, Part 1.” Using AI software, they were able to reconstruct the song from the brain recordings. This is the first time a song has been reconstructed from intracranial electroencephalography recordings.
Why does this matter?
By capturing the musicality of speech through neural signals, this research presents an innovative application of AI that could redefine how we interact and communicate, particularly for those who struggle with traditional modes of communication.
Saudi Arabia and UAE join the race for scarce Nvidia chips
Saudi Arabia has purchased at least 3,000 of Nvidia’s H100 chips at $40,000 apiece, while UAE has ordered a fresh batch of semiconductors to power its LLM. This signals the Gulf states’ intention to become major players in AI by buying up thousands of Nvidia’s GPUs which are vital in powering the boom in generative AI that has swept markets this year.
Why does this matter?
This makes them the latest to join the ever-growing queue of buyers for Nvidia chips to power AI ambitions. But will Nvidia be able to produce enough GPUs to meet the massive demand? It was reported in June that Nvidia GPUs are already in short supply (and very expensive).
Snapchat’s AI chatbot creates unexpected chaos
Snapchat users reported an unexpected video posted on the My AI chatbot’s Story, which some interpreted as showing a corner between a ceiling and a wall.
The unexpected post led to concerns and fears among users, with some believing the AI feature had become sentient or evolved, prompting some to delete the app.
Snapchat described the event as a “temporary outage”, which has since been resolved, and the AI chat feature temporarily stopped responding during this period.
Exploring the Power of Mojo Programming Language
Mojo is a new programming language that combines the usability of Python with the performance of C. It is designed to be the perfect language for developing AI models and applications. Mojo is fast, efficient, easy to use, and open source. Mojo is based on the LLVM (Low Level Virtual Machine) compiler infrastructure, which is one of the most advanced compiler frameworks in the world right now. Mojo uses a new type of system that allows for better performance and error checking. Mojo has a built-in autotuning system that can automatically optimize your code for the specific hardware that you are using.
Genmo is an artificial intelligence-driven video generator that takes text beyond the two dimensions of a page. Algorithms from natural language processing, picture recognition, and machine learning are used to adapt written information into visual form. It can turn text, pictures, symbols, and emoji into moving images. Background colors, characters, music, and other elements are just some of how the videos can be personalized. The movie will include the text and any accompanying images that you provide. The videos can be shared on many online channels like YouTube, Facebook, and Twitter. Videos made by Genmo’s AI can be used for advertising, instruction, explanation, and more. It’s a fantastic resource for companies, groups, and people who must rapidly and cheaply make interesting movies.
D-ID is a video-making platform powered by artificial intelligence that makes producing professional-quality videos from text simple and quick. Using Stable Diffusion and GPT-3, the company’s Creative RealityTM Studio can effortlessly create videos in over a hundred languages. D-ID’s Live Portrait function makes short films out of still images, and the Speaking Portrait function gives a speech to written or spoken text. Its API has been refined with the help of tens of thousands of videos, allowing it to generate high-quality visuals. Digiday, SXSW, and TechCrunch have all recognized D-ID for their ability to help users create high-quality videos at a fraction of the expense of traditional approaches.
The LeiaPix Converter is a web-based, no-cost service that changes regular photographs into 3D Lightfield photographs. It employs AI to turn your images into lifelike, immersive 3D environments. Select the desired output format and upload your picture to LeiaPix Converter. The converted file can be exported in several forms, including the Leia Image Format, Side-by-Side 3D, Depth Map, and Lightfield Animation. The LeiaPix Converter’s output is great quality and straightforward to use. It’s a fantastic way to give your pictures a new feel and make unique visual compositions. It does a 3D Lightfield conversion from a 2D image. Leia Image Format, Side-by-Side 3D, Depth Map, and Lightfield Animation are only a few of the supported export formats that bring about excellent outcomes. Depending on the size of the image, the conversion procedure could take a while. The quality of your original photograph will affect the final conversion outcomes. Because the LeiaPix Converter is currently in beta, it may include problems or have functionality restrictions.
A new open-source framework called instaVerse makes building your dynamic 3D environments easy. The background can be generated in response to AI cues, and players can then create their avatars to explore it. The first step in making a world in InstaVerse is picking a premade layout. Forests, cities, and even spaceships are just some of the many premade options available. After selecting a starter document, an AI assistant will guide you through the customization process. A forest with towering trees and a flowing river are just one of the many landscapes instaVerse may create at your command. Characters can also be generated in your universe. Humans, animals, and even robots are all included in the instaVerse cast of characters. Once a character has been created, you can use the keyboard or mouse to direct its actions. While InstaVerse is still in its early stages, it shows great promise as a robust platform for developing interactive 3D content. It’s simple to pick up and use and lets you make your special universes.
Sketch is a web app for turning sketches into GIF animations. It’s a fun and easy method to make unique stickers and illustrations to share on social media or use in other projects. Using Sketch is as easy as posting your drawing online. Then, you may utilize the drawing tools to give your work some life with some animation. Objects can be repositioned, recolored, and given custom sound effects. You can save your finished animation as a GIF after you’re satisfied. Sketch is a fantastic program for both young and old. It’s a terrific opportunity to show off your imagination and get a feel for the basics of animation simultaneously. In terms of ease of use, Sketch is excellent. Sketch makes it easy to create beautiful animations, even if you have no prior experience with the medium. With Sketch’s many tools, you can design elaborate and intricate animations. You can save your finished animation as a GIF after you’re satisfied. After that, your animation is ready for sharing or further use.
NeROIC can reconstruct 3D models from photographs as an element of AI technology. NeROIC, created by a reputable tech company, has the potential to transform our perceptions and interactions with three-dimensional objects radically. NeROIC can create a 3D model of the user’s intended message using an approved image. The video-to-3D capabilities of NeROIC are comparable to its image-to-3D capability. This means a user can create an interactive 3D setting from a single video. Because of this, creating 3D scenes is faster and easier than ever.
The discipline of computer science concerned with creating 3D models from 2D photographs is advancing quickly. Deep learning-based techniques may be used to train point clouds and 3D meshes to depict real-world scenes better. A potential method, DPT Depth Estimation, employs a deep convolutional network to read depth data from a picture and generate a point cloud model of the 3D object. DPT Depth Estimation uses monocular photos to input a deep convolutional network pre-trained on data from various scenes and objects. Following data collection, the web will use the information to create a point cloud from which 3D models can be made. When compared to conventional techniques like stereo-matching and photometric stereo, DPT’s performance can surpass a human’s. Because of its fast inference time, DPT is a promising candidate for real-time 3D scene reconstruction.
RODIN is quickly becoming the go-to 2D-to-3D generator in artificial intelligence. The creation of 3D digital avatars is now drastically easier and faster than ever before, thanks to this breakthrough. Creating a convincing 3D character based on a person’s likeness has always been more difficult. RODIN is an artificial intelligence-driven technology that can generate convincing 3D avatars using private data such as a client’s photograph. Customers are immersed in the action by seeing these fabricated avatars in 360-degree views.
That part at least seems pretty clear beyond a shadow of a doubt: Generative Enhanced Multimodal Intelligent Network Interface.
The word “Gemini” comes from Latin and means “twins” in German. Some possible meanings in the context of Google’s AI system:
Gemini combines two components: Text and image processing. It is, in a sense, a “twin system.”
Gemini could refer to the „twins“ Sergey Brin and Larry Page, the founders of Google.
Astrology assigns communication strength and flexibility to the zodiac sign Gemini. Gemini as an AI assistant aims to adapt linguistically and situationally.
The name suggests a dual strength or ability. Gemini aims to unite Google’s text and image AI to outperform the competition.
As a twin system, Gemini combines different perspectives and approaches, similar to different human characters. So the name is both an allusion to the system’s integrative capabilities and a promising indication of Google’s ambitions with this AI product.
Why is Google superior?
To do that, you have to understand WHAT treasure trove of data Google is actually sitting on. Here are a few facts:
Google, through its various services such as Google Search, YouTube and others, has an enormous amount of data that is very useful for developing AI systems.
On YouTube alone, over 500 hours of video material are uploaded every day, according to Statista. The total video database is over 30 million hours of video. The subtitles and transcripts of these videos give Google a gigantic text dataset for training language models.
According to a report by ARK Invest, Google owns over 130 exabytes of data. For comparison, 1 exabyte is equal to 1 billion gigabytes. This means that the entire data set comprises more than 130,000,000,000,000,000 bytes of information.
Google Search accounts for a large part of this data. Google says it processes over 40,000 search queries per second. That’s over 3.5 trillion search queries per year. From these queries and the clicked results, Google gains further insights.
Overall, it shows that Google has virtually inexhaustible data resources for AI research. Both the breadth of different types of data and the sheer volume should give Google a significant edge in the AI field.
Google – The Research Giant
In 2020, Google published over 1300 artificial intelligence research papers, according to the Papers with Code database. In 2021, Google increased the number of publications significantly again to over 2000 papers on AI and machine learning.
Topics included:
Computer Vision (image recognition)
Natural Language Processing (NLP)
Speech Recognition
reinforcement learning
Robotics
Multimodal AI
Recommender Systems
Applications in medicine
With over 3300 AI publications in 2020 and 2021, Google has greatly expanded its research output in artificial intelligence. The company is one of the most active players in this research field. This intensive work over the past few years is now being incorporated into the development of Gemini.
According to the AI publication database Papers with Code, Google published more than 1,500 artificial intelligence research papers in 2022 alone. That’s far more than other tech corporations like Meta or Microsoft.
This is a partial selection of Google’s most groundbreaking developments in AI in recent years. The list shows the enormous range of research from machine learning and computer vision to robotics and autonomous systems.
AlphaGo: Go game AI that defeated world champion Lee Sedol in 2016.
BERT (Bidirectional Encoder Representations from Transformers): breakthrough language model for NLP from 2018.
PaLM (Pathways Language Model): enormous language model with 540 billion parameters from 2022
PaLM-SayCan: variant of PaLM that can carry on human-like conversations
Imagen: image generation AI for realistic and creative images
MusicLM: AI for music composition and production
RLHF (Reinforcement Learning with Human Feedback): Reinforcement learning with human feedback
Model Based RL: reinforcement learning with explicit models of the environment
RobustFit: Robust neural network against data noise
T5: Text-to-text transfer transducer for various NLP tasks
ViT (Vision Transformer): Image recognition with Transformer architecture
WAYMO: Autonomous driving and robot cab service
ProteinFold: Protein structure prediction with Deep Learning
FLOOD: AI for flood prediction and prevention
SLIDE: pixel-level image segmentation
Switch Transformers: efficient architecture for very large transformers
MuZero: reinforcement learning without environmental model in games
Meena: conversational AI from 2020
DALL-E & DALL-E 2: text-to-image generation.
When you look at the sheer amount of data Google has collected over the years, it initially makes you dizzy. Over 500 hours of video footage are uploaded to YouTube every day. The total video database is over 30 million hours. Add to that countless search queries, texts, images and conversations. It’s an almost unimaginable amount of data.
Coupled with intensive research activity in the AI field, it adds up to enormous potential. In recent years, Google has produced groundbreaking innovations such as the BERT language model, the AlphaGo Go AI, and the DALL-E image generator. When you put all these puzzle pieces together, things take on almost frightening proportions.
Project: Google Gemini
With the new Gemini AI system, Google now seems to have bundled the essence of these years of data aggregation and research. If the company succeeds in combining all of its AI developments and treasure trove of data in this system, it would be a demonstration of the sheer power of innovation. It will be interesting to see whether Gemini can deliver on this promise. In any case, the expectations are huge – here what we know and what the rumors say:
Facts Google Gemini
There are already some facts from the Google Blog:
Gemini is supposed to be released this fall
Gemini combines text and image generation
Can create contextual images based on text generation
Has been trained with YouTube transcripts
Google lawyers are monitoring the training to avoid copyright issues
Gemini is said to have multiple modalities, e.g., text, image, audio, video
Sergey Brin is involved in development
Rumors
From Reddit and countless other sources on the web, there could be other features as well:
Gemini is said to be capable of AI image understanding and modification
Is said to combine text capabilities like GPT-4 with image generation
Has been developed from the ground up as a multimodal model
Could handle audio, video, 3D renderings, graphics, etc.
Shall learn with user interactions and thus become effective AGI
Architecture could enable lifelong learning
There are concerns about privacy and information leaks between users
Google Gemini and the (then new) AI market:
The AI market situation is likely to change significantly with the introduction of Google Gemini:
For OpenAI:
Strong new competitor for ChatGPT and DALL-E.
Google has significantly more resources and data
OpenAI could lose market share and come under pressure
For Anthropic:
Claude must stand up to Google Assistant with Gemini
Advantage due to focus on security and control
Risk of falling behind
For Microsoft:
Partnership with OpenAI important to compete with Google
Microsoft must further develop Azure AI services
Advantage due to strong cloud infrastructure
For others:
Startups could have a very hard time against Google
Consolidation in the market possible
Significantly higher innovation speed
Overall, competitive pressure in the AI market will increase sharply. With its resources, Google is in a very good starting position to take a leading role with Gemini. It will be more difficult for other providers to keep pace with Google. It remains to be seen whether the high expectations for Gemini are justified.
Google Gemini Conclusion
Google Gemini seems to be a very ambitious AI project that should give the company a competitive edge. The combination of different modalities in one model is new and could improve AI capabilities tremendously. However, there are still many unanswered questions regarding the specific capabilities and data security. The release this fall will show whether Google can deliver on its promise to outperform the competition. Much is still speculation, but expectations are high.
#ai #ki #google #gemini #text #image #multimodal
Artificial intelligence steps in to assist dementia patients with ‘AI Powered Smart Socks’
People suffering from dementia could live more independently thanks to a pair of AI-powered socks that can track everything from a patient’s heart rate to movement.
Called “SmartSocks,” the AI-powered apparel was created in partnership between the University of Exeter and researchers at the start-up company Milbotix, according to SWNS. The socks can monitor a patient’s heart rate, sweat levels and motion to prevent falls while also promoting independence for those with dementia.
“I came up with the idea for SmartSocks while volunteering in a dementia care home,” SmartSocks creator Zeke Steer, CEO of Milbotix, told SWNS. “The current product is the result of extensive research, consultation and development.”
Steer’s great-grandmother suffered from dementia, which also helped spark the creation of the socks.
“The foot is actually a great place to collect data about stress, and socks are a familiar piece of clothing that people wear every day; our research shows that socks can accurately recognize signs of stress, which could really help not just those with dementia but their caregivers, too,” Steer, who has a background in robotics and AI, told SWNS.
The socks send the data collected from the patient to an app, which flags caregivers when the patient appears to be in distress. The warning could prevent falls and even tragedies as caregivers can respond to a patient before their stress escalates.
“I think the idea of SmartSocks is an excellent way forward to help detect when a person is starting to feel anxious or fearful,” said Margot Whittaker, director of nursing and compliance at Southern Healthcare in the U.K.
A handful of care homes overseen by Southern Healthcare, including The Old Rectory in Exeter, are already testing the tech-powered socks on patients, who report they are happy with how easy the socks are to use.
“Anything that’s simple and easy to do, and is improving our look at life as a whole, I’m happy with,” dementia patient John Piper, 83, told the BBC.
The socks do not need to be recharged, according to Milbotix’s website, and can be machine washed.
There are other products on the market that can also track a dementia patient’s heart rate or sweat levels, but they often come in the form of wristbands and watches, which can pose issues to those with dementia.
“Wearable devices are fast becoming an important way of monitoring health and activity,” Imperial College London’s Health and Social Care Lead Sarah Daniels told SWNS. “At our center, we have been trialing a range of wristbands and watches. However, these devices present a number of challenges for older adults and people affected by dementia.”
Daniels said wristbands or watches often don’t hold long charges and are taken off by patients and then lost.
“SmartSocks offer a new and promising alternative, which could avoid many of these issues,” Daniels said.
The University of Exeter is investigating how beneficial the socks are for dementia patients.
Artificial intelligence platforms are revamping health care across many disciplines, including another U.K.-based system called CognoSpeak, which can monitor speech patterns in a bid to detect early signs of dementia or Alzheimer’s.
U.K.-based start-up SmartSocks has developed hosiery that can monitor a dementia patient’s heart rate, motion and sweat levels with AI and alert caregivers to potential problems.
GPT-4 Code Interpreter can enhance math skills with code-based self-verification – OpenAI’s GPT-4 Code Interpreter’s remarkable performance in math datasets is largely attributed to its step-by-step code generation and dynamic solution refinement based on code execution outcomes. Expanding on this understanding, new research has introduced the innovative explicit code-based self-verification (CSV) prompt, which leverages GPT4-Code’s advanced code generation mechanism. This prompt guides the model to verify the answer and then reevaluate its solution with code. – The approach achieves an impressive accuracy of 84.32% on the MATH dataset, significantly outperforming the base GPT4-Code and previous state-of-the-art methods.
AI just reconstructed a Pink Floyd song from brain activity, and it sounds shockingly clear – Neuroscientists recorded electrical activity from areas of the brain as patients listened to the Pink Floyd song “Another Brick in the Wall, Part 1.” Using AI software, they were able to reconstruct the song from the brain recordings. This is the first time a song has been reconstructed from intracranial electroencephalography recordings.
Saudi Arabia and UAE join the race for scarce Nvidia chips – Saudi Arabia has purchased at least 3,000 of Nvidia’s H100 chips at $40,000 apiece, while UAE has ordered a fresh batch of semiconductors to power its LLM. This signals their intention to become major players in AI.
OpenAI acquires Global Illumination to work on core products, including ChatGPT – Its team leverages AI to build creative tools, infrastructure, and digital experiences. It previously designed and built products early on at Instagram and Facebook and has made significant contributions at YouTube, Google, Pixar, Riot Games, and other notable companies.
McKinsey unveils its own generative AI tool for employees: Lilli – It is a chat application for employees designed that serves up information, insights, data, plans, and even recommends the most applicable internal experts for consulting projects, all based on 100K+ documents and interview transcripts.
Opera’s iOS web browser will now include Aria – The AI assistant, Aria, is Opera’s browser AI product built in collaboration with OpenAI, integrated directly into the web browser, and free for all users.
Adobe Express with AI Firefly app is available worldwide – The web app is now out of beta and can be used free of charge in web browsers.
The Associated Press releases guidelines for Generative AI to its journalists
UK is using AI road safety cameras to detect potential driver offenses in passing vehicles
The founder of Centricity, a data analytics firm using AI, is indicted for defrauding investors by manipulating financial data.
Leaders with a Montana digital academy say bringing artificial intelligence to high schools is an opportunity to embrace the future.
Google said to be testing new life coach AI for providing helpful advice to people.
Alibaba Cloud MagicBuild Community has launched the digital human video generation tool called LivePortrait. It can generate digital human videos from photos, text, or voice, which can be applied in scenarios such as live broadcasting and corporate marketing.
Are physical SIMs about to be a thing of the past? Jump into the latest, and discover eSIMs #sponsored
Latest Sport Football Soccer News and Trends on August 17th, 2023
Atletico Madrid takes the alleged ‘threat’ of João Félix terminating his contract as a joke. If he wants to do so, he will have to pay his €350m release clause. Link
BREAKING: Theo Walcott is set to retire. Walcott, 34, who left Southampton at the end of last season, scored more than 100 goals for Arsenal and won 47 England caps. Link
From epic open-world adventures to mind-bending puzzles, these are the best iOS games to play on the upcoming iPhone 15.
Unraveling August 2023: August 16th, 2023
Latest AI News and Trends on August 16th, 2023
GPT-4 to replace content moderators
OpenAI aims to use its GPT-4 to solve the challenge of content moderation at scale. Also, they already used GPT-4 to develop and refine their own content policies. It provides three major benefits: consistent judgments, faster policy development, and improved worker well-being. However, perfect content moderation remains elusive, as both humans and machines make mistakes, particularly in handling misleading or aggressive content.
GPT-4 can interpret complex policy documentation and adapt instantly to updates, reducing the cycle from months to hours. This AI-assisted approach offers a positive future for digital platforms, where AI can help moderate online traffic and relieve the burden on human moderators.
Why does this matter?
GPT-4 can alleviate content moderation challenges and improve the efficiency and effectiveness of content moderation. This could be a solution for platforms like Facebook and Twitter, who’ve been grappling with content moderation for ages. OpenAI’s this approach could also appeal to smaller companies lacking resources.
Shepherd is a language model designed to critique and improve the outputs of other language models. It uses a high-quality feedback dataset to identify errors and provide suggestions for refinement. Despite its smaller size, Shepherd’s critiques are either equivalent or preferred to those from larger models like ChatGPT. In evaluations against competitive alternatives, Shepherd achieves a win rate of 53-87% compared to GPT-4.
Shepherd outperforms other models in human evaluation and is on par with ChatGPT. Shepherd offers a practical and valuable tool for enhancing language model generation.
Why does this matter?
Despite Shepherd’s smaller size, its critiques match or surpass those of larger models like ChatGPT, with a win rate of 53-87% against GPT-4. It excels in human evaluations and offers practical value in improving language model generation.
Microsoft now offers OpenAI’s ChatGPT model in its Azure OpenAI service, allowing developers and businesses to integrate conversational AI into their applications. ChatGPT can be used to power custom chatbots, automate emails, and provide summaries of conversations.
Azure OpenAI users can access a preview of ChatGPT starting today, with pricing set at $0.002 for 1,000 tokens. ChatGPT on Azure solution accelerator is an enterprise option. This solution provides a similar user experience to ChatGPT but is offered as your private ChatGPT.
Microsoft Azure ChatGPT offers several benefits to organizations:
Ensures data privacy with built-in guarantees and isolation from OpenAI-operated systems.
Allows full network isolation and offers enterprise-grade security controls.
Enhances business value by integrating internal data sources and services like ServiceNow.
Why does this matter?
Amid the excitement around ChatGPT, Microsoft has cleverly introduced an enterprise version to meet strong market demand. By prioritizing security, Azure simplifies and enhances companies’ access to AI advantages. Also, Microsoft’s move aims to boost productivity through code editing, task automation, and more and offers enterprises a more secure way to share their data with AI.
Nvidia’s stock rises 7% as investors see its GPUs remaining dominant in powering large language models.
Morgan Stanley reiterates Nvidia as a “Top Pick” due to strong earnings, AI spending shift, and ongoing supply-demand imbalance.
Despite recent fluctuations, Nvidia’s stock has tripled in 2023, and analysts anticipate long-term benefits from AI and favorable market conditions.
The Strength and Realism of AI Models While artificial intelligence models demonstrate immense computational power, there’s a debate regarding their biological plausibility. How do these digital frameworks compare to the natural intelligence of living organisms? Are they accurate representations or mere simulations?
Transportation Systems: The Paradox of Choice More choices in transportation systems might seem beneficial, but there’s a hidden challenge. With increased variety comes complexity, leading to inefficiencies and potential gridlocks.
AI’s Role in Pinpointing Cancer Origins Recent advancements in AI have developed a model that can assist in determining the starting point of a patient’s cancer, a crucial step in identifying the most effective treatment method. [Read more at MedicalTechNews.com]
AI’s Defense Against Image Manipulation In the era of deepfakes and manipulated images, AI emerges as a protector. New algorithms are being developed to detect and counter AI-generated image alterations. [Read more at DigitalSafetyWatch.com]
Streamlining Robot Control Learning Researchers have uncovered a more straightforward approach to teach robots control mechanisms, making the integration of robotics into various industries more efficient.
Accelerated Robotics Training Techniques A revolutionary methodology promises to slash the time required to instruct robots, optimizing their utility and deployment speed in multiple applications.
Armando Solar-Lezama: The Beacon of Computing Armando Solar-Lezama has been honored as the inaugural Distinguished Professor of Computing, acknowledging his invaluable contributions to the world of computer science.
Efficient Planning for Household Robots with AI AI integration has enabled household robots to plan tasks more efficiently, cutting their preparation time by half and allowing for more seamless operations in domestic environments.
The ChatGPT Impact: Boosting Writing Productivity A recent study highlights how ChatGPT enhances workplace productivity, particularly in writing tasks. The AI-driven tool provides a significant advantage for professionals in diverse sectors.
Reimagining Data Privacy in the Modern Era Data privacy is evolving, and it’s time to approach it with a fresh perspective. As digital footprints expand, there’s an urgent need to revisit and redefine what personal data protection means.
Daily AI News on August 16th, 2023
OpenAI’s GPT-4 for more reliable and higher quality content moderation – OpenAI aims to use its GPT-4 to solve the challenge of content moderation at scale. GPT-4 could replace human moderators, offering similar accuracy and more consistency. OpenAI has already used GPT-4 to develop and refine its own content policies. – It provides three major benefits: consistent judgments, faster policy development, and improved worker well-being. While AI has been used for content moderation before, OpenAI’s approach could be appealing to smaller companies lacking resources.
Microsoft launches ChatGPT for enterprises with Azure – Microsoft is now offering OpenAI’s ChatGPT model in its Azure OpenAI service, allowing developers and businesses to integrate conversational AI into their applications. ChatGPT can be used to power custom chatbots, automate emails, and provide summaries of conversations. – Azure OpenAI users can access a preview of ChatGPT starting today, with pricing set at $0.002 for 1,000 tokens and it promises more control and privacy compared to the public model.
Google is progressing with new AI updates! – Search experience adds AI-powered summaries, definitions, and coding improvements. In addition it will include related diagrams or images for various topics, color-coded syntax highlighting for code snippets, making it easier for programmers to understand and debug generated code. – Google Photos adds a scrapbook-like Memories view feature aided by AI which allows users to relive and share their most memorable moments. The feature creates a scrapbook-like timeline that includes trips, celebrations, and daily moments with loved ones. The new Memories view is launching today for U.S. users and is similar to a combination of Stories and Facebook Memories.
Amazon using AI to enhance product reviews – Amazon is tapping into generative AI to create handy highlights that collects key points from customer reviews which will help shoppers quickly gauge product review. – The feature is part of ongoing efforts to improve utility of 125M+ reviews from shoppers. It uses only trusted reviews from verified purchases, and Amazon.
WhatsApp test beta upgrade with new feature ‘custom AI-generated stickers’ – The feature is currently available to a limited number of beta testers, includes a “Create” button under the stickers tab, which opens a keyboard for users to type prompts for the AI model to generate custom stickers. The feature is a server-side change and is currently only available in version 2.23.17.8 of the beta version.
Apple’s AI advancements in the last few months
Don’t sleep on Apple’s AI plans. Here’s how they’ve been slowly ramping up their AI efforts in the last few months.
Apple’s AI-powered health coach might soon be at your wrists Apple is reportedly developing an AI-powered health coaching service called Quartz, aimed at helping users improve their exercise, eating habits, and sleep quality. The service will use AI and data from the user’s Apple Watch to create personalized coaching programs, with plans to introduce a monthly fee. The company is also working on emotion-tracking tools and plans to launch an iPad version of the iPhone Health app this year.
Apple enters the AI race with new features Apple announced a host of updates at the WWDC 2023. Yet, the word “AI” was not used even once, despite today’s pervasive AI hype-filled atmosphere. The phrase “machine learning” was used a couple of times. (And AI is nothing but machine learning). However, here are a few announcements Apple made that use AI as the underlying technology.
Apple Vision Pro, a revolutionary spatial computer that seamlessly blends digital content with the physical world. It uses advanced ML techniques.
Upgraded Autocorrect in iOS 17 that is powered by a transformer language model for improved prediction capabilities.
Improved Dictation in iOS 17 that leverages a new speech recognition model to make it even more accurate.
Live Voicemail that turns voicemail audio into text on the fly, which is powered by a neural engine.
Personalized Volume, which uses ML to understand environmental conditions and listening preferences over time to automatically fine-tune the media experience.
Journal, a new app for users to reflect and practice gratitude, uses on-device ML for personalized suggestions to inspire entries.
Apple Trials a ChatGPT-like AI Chatbot Apple is developing AI tools, including its own large language model called “Ajax” and an AI chatbot named “Apple GPT.” They are gearing up for a major AI announcement next year as it tries to catch up with competitors like OpenAI and Google.
Apple bets big on AI Apple’s CEO Tim Cook has stated that AI and ML are embedded in every company product. This comes after concerns were raised about Apple’s lack of discussion on its AI plans while competitors have been actively incorporating the technology into their products. He also emphasized that AI is central to the design of Apple’s products, contradicting suggestions that the company has not yet integrated the technology.
Apple gearing up for an AI showdown Apple has reportedly ordered servers from Foxconn Industrial Internet, a division of its supplier Foxconn, for the testing and training of AI services. The servers are specifically for Apple’s AI work, which has been a focus for the company for years. While Apple does not currently have a ChatGPT-like app for external use, it is believed that this division of Foxconn already supplies servers to ChatGPT OpenAI, Nvidia, and Amazon Web Services. The news comes amidst reports about Apple’s plans to compete in the AI chatbot market.
The U.S. Consumer Financial Protection Bureau (CFPB) plans to regulate data brokers selling personal data due to concerns about their impact on privacy, including sensitive data from vulnerable groups.
CFPB aims to prevent illegal collection and sharing of personal data by data brokers in the surveillance industry.
The proposal expands coverage under the Fair Credit Reporting Act to include data derived from payment histories, personal income, and criminal records, addressing concerns such as credit header data disclosure.
Tesla unveils cheaper Model S and Model X variantsLINK
Tesla introduces lower-priced options for the Model S and Model X with reduced range.
The “standard range” trim brings the Model S starting price to $78,490 with 320 miles of range and the Model X starting price to $88,490 with 269 miles of range.
This trim, previously discontinued, likely uses the same battery pack with a software lock, and Tesla may offer range unlocking for an additional fee.
Singapore pioneers in stablecoin crypto regulationLINK
Singapore’s financial regulator has finalized rules for stablecoins, making it one of the first jurisdictions to do so globally.
Stablecoins are digital currencies designed to maintain a constant value against fiat currency, with a market value of around $125 billion and dominated by tokens like USDT and USDC.
The Monetary Authority of Singapore’s framework outlines requirements including holding reserves in low-risk assets, timely redemption, and proper user disclosures for stablecoins mimicking the Singapore dollar or other G10 currencies.
Amazon Pharmacy offers major savings on insulinLINK
Amazon Pharmacy offers automatic coupons to help uninsured insulin-requiring patients save on medication costs.
The digital pharmacy shows pricing with and without insurance, estimates savings with eligible coupons, and simplifies the process compared to existing coupon programs.
Amazon Pharmacy’s initiative has been praised by healthcare advocates and aims to improve access to affordable treatments, but manufacturer coupons are not available for patients benefiting from certain healthcare programs.
Other Tech news you might like
Apple will soon start making settlement payments to claimants of the “Batterygate” class-action lawsuit, with potential payments of up to $65 per person.LINK
YouTube is removing cancer treatment content that’s “harmful or ineffective,” implementing new guidelines to remove unproven treatments and harmful advice.LINK
California regulators approved round-the-clock robotaxi service in San Francisco for Waymo and Cruise, but a group of Cruise vehicles caused a traffic backup, highlighting challenges.LINK
Microsoft is implementing an eight-strike suspension policy for Xbox community standards violations, scaling suspensions based on the number of strikes, with players able to appeal and view enforcement history.LINK
Unraveling August 2023: August 15th, 2023
Latest AI News and Trends on August 15th, 2023
Do It Yourself Custom AI Chatbot for Business in 10 Minutes (Open Source)
If you’re looking to “train” a custom chatbot on your data (SOPs, legal docs, financial reports, etc), I’d strongly suggest checking out AnythingLLM. It’s the first chatbot with enterprise-grade privacy & security. When using ChatGPT, OpenAI collects your data including: – Prompts & Conversations – Geolocation data – Network activity information – Commercial information e.g. transaction history – Identifiers e.g. contact details – Device and browser cookies – Log data (IP address etc.) However, if you use their API to interact with their LLMs like gpt-3.5 or gpt-4, your data is NOT collected. This is exactly why you should **build your own private & secure chatbot**. That may sound difficult, but Mintplex Labs (backed by Y-Combinator) just released AnythingLLM, which gives you the ability to build a chatbot in 10 minutes without code. AnythingLLM provides you with the tools to easily build and manage your own private chatbot using API keys. Plus, you can expand your chatbot’s knowledge by importing data such as PDFs, emails, etc. This can be confidential data as only you have access to the database. ChatGPT currently allows you to upload PDFs, videos and other data to ChatGPT via vulnerable plug-ins, BUT there is no way to determine if that data is secure or even know where it’s stored. Easily build your own business-compliant and secure chatbot at useanything.com. All you need is an OpenAI or Azure OpenAI API key. Or, if you prefer using the open source code yourself, here’s the GitHub repo: https://github.com/Mintplex-Labs/anything-llm.
AI powered tools for the recruitment industry
AI-driven recruiting and retention strategies utilize data-driven strategies for better candidate experiences and better hiring decisions. Here’s a list of a few tools that are useful for this purpose : – Conversational AI To Recruit And Retain At Scale | Humanly.io : It is designed for high scale hiring in organizations. It enhances candidate engagement through automated chat interactions.
– MedhaHR : It’s an AI-driven healthcare talent sourcing platform that automates resume screening, provides personalized job recommendations, and offers cost-effective solutions.
– ZappyHire : It offers features such as candidate sourcing, resume screening, automated communication, and collaborative hiring.
– Sniper AI : It uses AI algorithms to source potential candidates, assess their suitability, and integrates with ATS for workflow optimization.
– PeopleGPT : PeopleGPT, developed by Juicebox (YC S22), is a tool that simplifies the process of searching for people data. Recruiters can input specific queries to find potential candidates. Which tools have you been using, and more importantly is AI really helping you with recruitment? More resources along with their pricing plans here
American companies are vigorously seeking AI specialists, leading to soaring salaries for high-demand roles. Amidst this recruitment frenzy, some organizations are offering nearly a million-dollar salary, especially to those experienced in AI.
Surge in AI Talent demand and salaries
American firms are hunting for AI experts, with some offering salaries nearing a million dollars.
Industries like entertainment and manufacturing want data scientists and machine-learning specialists.
Competition is fierce, with companies like Accenture investing in internal training and others considering acquisition of AI startups for talent.
The compensation landscape for AI roles
As AI expertise becomes more sought-after, compensation packages are rising.
Companies are offering mid-six-figure salaries, bonuses, and stock grants to lure experienced professionals.
While top positions like Netflix’s machine-learning platform product manager can reach up to $900,000 in total compensation, othersalike a prompt engineer might average $130,000 annually.
How to Manage Your Remote Team Effectively with ChatGPT?
Leading a remote team comes with unique challenges, from ensuring clear communication to fostering a sense of community. ChatGPT can be your expert consultant, offering suggestions based on best practices for remote team management.
You are a seasoned consultant in remote team management. I am the leader of a remote team working on a [define project]. I need advice on how to effectively manage my team, ensure clear communication, monitor progress, and maintain a positive team culture. Your suggestions should include strategies for scheduling and conducting virtual meetings, task assignment, progress tracking tools, and methods to promote team building in a virtual setting.
I asked ChatGPT to remove password protection from an Excel document, and it worked flawlessly
How are you uploading an excel document to chat gpt?
Using ChatGPT code interpreter: It’s a feature for GPT plus member as the old “bing search” which got disabled, You have code interpreter now where you can directly upload files.
Can it analyze conversations/texts? Yes it can analyse data and even give u back charts and feedback for gpt plus users.
Johns Hopkins Engineers and Cancer Researchers have collaboratively pioneered a breakthrough in personalized cancer therapy with their cutting-edge deep-learning technology.
Summary: Microsoft Azure allows organizations to run ChatGPT within their network for smoother work experiences. Think of it as your private, controlled, and extra valuable AI assistant. (source)
Key points:
Azure allows companies to run ChatGPT privately on their own networks, touting built-in data isolation from OpenAI.
The model connects to internal data services and sources, and is available on GitHub to install and deploy.
Benefits include privacy, control, and unique business value through internal data integration.
Why It Matters: For enterprises, this merger between ChatGPT and Azure opens a new realm of possibilities, with the cozy feeling of privacy and control. It’s more than a tech tool; it’s a tailored solution that could redefine how businesses work with AI.
Apple’s AI-powered health coach might soon be at your wrists
Apple is reportedly developing an AI-powered health coaching service called Quartz, aimed at helping users improve their exercise, eating habits, and sleep quality. The service will use AI and data from the user’s Apple Watch to create personalized coaching programs, with plans to introduce a monthly fee. The company is also working on emotion-tracking tools and plans to launch an iPad version of the iPhone Health app this year.
Why does this matter?
It’s only a matter of time before AI is deployed on IoT devices such as smartwatches. This confluence can definitely revolutionize our daily lives. AI can direct IoT devices to adapt and optimize settings based on external circumstances making them a lot more autonomous and helpful.
Apple announced a host of updates at the WWDC 2023. Yet, the word “AI” was not used even once, despite today’s pervasive AI hype-filled atmosphere. The phrase “machine learning” was used a couple of times. (And AI is nothing but machine learning). However, here are a few announcements Apple made that use AI as the underlying technology.
Apple Vision Pro, a revolutionary spatial computer that seamlessly blends digital content with the physical world. It uses advanced ML techniques.
Upgraded Autocorrect in iOS 17 that is powered by a transformer language model for improved prediction capabilities.
Improved Dictation in iOS 17 that leverages a new speech recognition model to make it even more accurate.
Live Voicemail that turns voicemail audio into text on the fly, which is powered by a neural engine.
Personalized Volume, which uses ML to understand environmental conditions and listening preferences over time to automatically fine-tune the media experience.
Journal, a new app for users to reflect and practice gratitude, uses on-device ML for personalized suggestions to inspire entries.
Why does this matter?
To the average user, AI can be scary. Perhaps it was Apple’s deliberate choice not to mention the word “AI”? Nevertheless, these updates and features demonstrate that Apple is indeed utilizing AI technologies in various aspects of its products and services, joining the likes of Google and Microsoft.
Apple is developing AI tools, including its own large language model called “Ajax” and an AI chatbot named “Apple GPT.” They are gearing up for a major AI announcement next year as it tries to catch up with competitors like OpenAI and Google.
The company has multiple teams developing AI technology and addressing privacy concerns. While Apple has been integrating AI into its products for years, there is currently no clear strategy for releasing AI technology directly to consumers. However, executives are considering integrating AI tools into Siri to improve its functionality and keep up with advancements in AI.
Why does this matter?
Apple’s development of AI tools, such as the language model “Ajax” and chatbot “Apple GPT,” signals the company’s efforts to catch up with competitors OpenAI and Google. The focus on addressing privacy concerns and the potential integration of AI into Siri shows Apple’s aim to enhance its product functionality and stay competitive.
Apple’s CEO Tim Cook has stated that AI and ML are embedded in every company product. This comes after concerns were raised about Apple’s lack of discussion on its AI plans while competitors have been actively incorporating the technology into their products. He also emphasized that AI is central to the design of Apple’s products, contradicting suggestions that the company has not yet integrated the technology.
Cook reassured that Apple has invested in AI for years, and this year’s Research & Development spending has hit $22.61 billion. They are also hiring dozens of AI jobs in the US, France, and China, looking to fill roles that could help build Gen AI tools.
Why does this matter?
This move signifies the potential for enhanced personalization and contextual relevance in user interactions, leading to a more intuitive and tailored experience within the Apple ecosystem. The seamless integration of AI may also pave the way for groundbreaking applications in health, home automation, and more. Ultimately redefining how users interact with and benefit from Apple’s ecosystem of products and services.
Apple has reportedly ordered servers from Foxconn Industrial Internet, a division of its supplier Foxconn, for the testing and training of AI services. The servers are specifically for Apple’s AI work, which has been a focus for the company for years. While Apple does not currently have a ChatGPT-like app for external use, it is believed that this division of Foxconn already supplies servers to ChatGPT OpenAI, Nvidia, and Amazon Web Services. The news comes amidst reports about Apple’s plans to compete in the AI chatbot market.
Why does this matter?
Apple’s this latest move to order servers from Foxconn’s division for AI testing and training has caught attention. While Apple hasn’t launched a ChatGPT-like app yet, the supplier’s involvement with ChatGPT OpenAI, Nvidia, and Amazon Web Services hints at potential AI ventures. Apple seems like a potentially new big player in the AI game.
The ‘SGE while browsing’ feature can break down a long web page into easy-to-read key points.
Daily AI News August 15th, 2023
Talon Aerolytics, a leading innovator in SaaS, Digital Twin capture services and AI technology, has announced ha its groundbreaking cutting-edge AI-powered computer vision platform enables wireless operators to visualise and analyse network assets using end-to-end AI and machine learning. Link
Beijing is poised to implement sweeping new regulations for artificial intelligence services this week, trying to balance state control of the technology with enough support that its companies can become viable global competitors. Link
Saudi Arabia and the United Arab Emirates are buying up thousands of the high-performance Nvidia chips crucial for building artificial intelligence software, joining a global AI arms race that is squeezing the supply of Silicon Valley’s hottest commodity. Link
OpenAI likely to go bankrupt by the end of 2024. Link
Latest Tech News on August 15th, 2023
Youtube algorithm flaws?
Personally I’ve always been a huge fan of youtube but I always thought that their algorithm have actually gotten worse since the 2010s.
Supposedly Google should have perfected the algorithm at making simple recommendations; they have teams working on it yet i could think of a few things that could improve it.
From my experience, youtube always recommends the same stuff. If you like one video or click on it, it would keep showing that channels videos until you’re bombarded by it. It rarely gives you anything new, or reminds you of old topics you enjoyed. Sometimes videos are just stuck there for weeks, when i’m clearly not watching it. Sometimes something i really want to watch disappears and never comes back again. Furthermore It’s other sections/buttons do not show the videos i mention above, but rather completely unrelated content.
Just off the top of my head, I can think of a few things – becoming more ambitious every refresh; recommend new topics more often; remind you of old topics you like more often.
YouTube announced a new policy for combatting medical misinformation on the video sharing platform
Latest World and Sport News on August 15th, 2023
Fulton County grand jury returns an indictment in 2020 election probe for Georgia. Link
The highest paid football players in the world in 2023 according to Le Parisien
After Al-Hilal move, Neymar leapfrogs Romelu Lukaku as the player with the highest combined transfer fee in football history.
Asked ChatGPT “Can you write an essay about web browsers but using a tone of a depressed teenager?” And this was the result
Ugh, like, seriously? Web browsers, man, they’re just like another thing we have to deal with in this messed up digital world. It’s like, we can’t even escape the internet, even if we wanted to. I mean, sure, web browsers are supposed to be all convenient and stuff, making it, like, easier for us to, you know, “surf” the internet. But honestly, it’s just one more thing on my list of things that stress me out.
First off, there’s like a gazillion web browsers out there. Chrome, Firefox, Safari, Edge – it’s like a popularity contest or something. Everyone’s like, “Use this one, it’s the best,” but then someone else is like, “Nah, that one sucks, use this one.” And, like, who even has the energy to care anymore? It’s like trying to pick the coolest outfit to wear, but for your computer. Can’t I just, like, not care and use whatever comes pre-installed?
And then there’s all these updates. Like, seriously, can’t they just leave me alone? Every time I want to, like, chill and watch some random videos, there’s this annoying pop-up telling me to update my browser. And I’m like, “Dude, I just updated you, like, last week. Can you give me a break?” It’s like they’re trying to control my life or something.
And don’t even get me started on cookies and privacy stuff. Like, I get it, they want to, like, track my every move and sell my info to, like, who knows who. But, hello, can a girl get some privacy? It’s like they’re stalking me, following me around, knowing all my secrets. It’s not like I asked for this, you know?
Oh, and the extensions. Like, yeah, I get it, they’re supposed to, like, make my life easier or whatever. But honestly, half the time I don’t even know what they do. It’s like going to a party and not knowing anyone – you’re just there, hoping for the best. And, of course, they slow down my browser, because why not add more misery to my life?
But you know what’s the worst? Those error messages. It’s like the browser is mocking me, laughing at my inability to even load a simple webpage. “Aw, you wanted to check your favorite blog? Too bad, here’s an error message just for you.” It’s like they’re out to get me, to ruin my day, to remind me that technology hates me.
So, yeah, web browsers are just another thing in this never-ending cycle of frustration and confusion. They’re like that friend who always says they’ll be there for you but ends up ghosting you when you really need them. Maybe one day they’ll figure themselves out and actually make my life better. But until then, I’ll just be here, rolling my eyes every time I open a new tab. Whatever, man.
People are having sex in self-driving cars, apparently. Link
Top physicist says chatbots are just ‘glorified tape recorders’ Link
Spain are just one step away from Women’s World Cup glory after their dramatic 2-1 semi-final win over Sweden on Tuesday and forward Salma Paralluelo said ‘La Roja’ had proved they have what it takes to be crowned champions.
LLM (Large Language Model) is a type of AI model designed to understand and generate human-like text. These models are trained on vast amounts of text data and use deep learning techniques, such as deep neural networks, to process and generate language.
LLMs are capable of performing various natural language processing (NLP) tasks, including
Language translation
Text summarization
Question-answering
Sentiment analysis
Generating coherent and contextually relevant responses to user inputs
They are trained on a wide range of textual data sources, such as books, articles, websites, and other written content, allowing them to learn grammar, vocabulary, and contextual relationships in language.
Examples of Large Language Models
Some of the most popular large language models are:
GPT-3 by OpenAI: GPT-3 is a large language model that was first released in 2020. It has been trained on a massive dataset of text and code, and it can generate text, translate languages, write different kinds of creative content, and answer your questions in an informative way.
T5 by Google AI: T5 is a large language model that was first released in 2021. It is specifically designed for text generation tasks, and it can generate text that is more accurate, consistent, and creative than smaller language models.
LaMDA by Google AI: LaMDA is a large language model that was first released in 2022. It is specifically designed for dialogue applications, and it can hold natural-language conversations with users.
PaLM by Google AI: PaLM is a large language model that was first released in 2022. It is the largest and most powerful language model ever created, and it can perform a wide range of tasks, including text generation, translation, summarization, and question-answering.
FlaxGPT by DeepMind: FlaxGPT is a large language model that was first released in 2022. It is based on the Transformer architecture, and it can generate text that is more accurate and consistent than smaller language models.
Large language models (LLMs) have a number of advantages over traditional machine learning models. These advantages include:
Improved accuracy and performance: LLMs can be trained on massive datasets of text and code, which allows them to learn the nuances of human language and generate more accurate and consistent results than traditional machine-learning models.
Increased efficiency: LLMs can automate many tasks that were previously done manually, such as text classification, summarization, and translation. This can save businesses time and money, and free up human workers to focus on more creative and strategic tasks.
Expanded possibilities: LLMs can be used to create new and innovative products and services. For example, they can be used to develop chatbots that can hold natural-language conversations with customers or to create virtual assistants that can help users with tasks such as scheduling appointments or finding information.
Enhanced creativity: LLMs can be used to generate creative text formats, such as poems, code, scripts, musical pieces, emails, letters, and more with endless possibilities. This can be used to improve the quality of content or to create new and innovative forms of art and entertainment.
Reduced bias: LLMs can be trained on datasets that are more diverse than traditional datasets, which can help to reduce bias in their results. This is important for businesses and organizations that want to ensure that their products and services are fair and equitable for all users.
Challenges of LLM
Large language models (LLMs) are a powerful new technology, but they also come with several challenges. These challenges include:
Data requirements: LLMs require massive datasets of text and code to train. This can be a challenge for businesses and organizations that do not have access to large datasets.
Computational resources: LLMs require a lot of computational resources to train and run. This can be a challenge for businesses and organizations that lack the necessary resources.
Interpretability: LLMs are often difficult to interpret. This makes it difficult to understand how they work and to ensure that they are not generating harmful or biased results.
Bias: LLMs can be biased, depending on the data they are trained on. This can be a challenge for businesses and organizations that have ensured that their products and services are fair and equitable for all users.
Safety: LLMs can be used to generate harmful or misleading content. This can be challenging for businesses and organizations having a reputation for safe and secure services.
Use cases of LLM
The future of LLM models is bright. As this technology continues to develop, we can expect to see even more innovative and groundbreaking applications for LLMs in the future.
Some of the promising applications of LLMs include:
Virtual Assistants: LLMs could be used to power virtual assistants that are even more human-like and helpful than they are today. These virtual assistants could be used to provide a wide range of services, such as scheduling appointments, finding information, and controlling smart home devices.
Content Generation: LLMs could be used to generate more engaging and informative content. This content could be used to improve the customer experience, educate users, and entertain people.
Translation: LLMs could be used to translate text from one language to another more accurately and efficiently than ever before. This could help businesses to reach a wider audience and to provide better customer service.
Research: LLMs could be used to conduct research in a wider range of fields, such as natural language processing, machine translation, and artificial intelligence. This could help to advance our understanding of these fields and to develop new and innovative applications.
Education: LLMs could be used to create personalized learning experiences for students. These experiences could be tailored to each student’s individual needs and interests.
Healthcare: LLMs could be used to diagnose diseases, develop new treatments, and provide personalized care to patients.
Art and entertainment: LLMs could be used to create new forms of art and entertainment. This could include poems, code, scripts, musical pieces, emails, letters, etc.
Now that we have gone through the examples of Large Language Models, let us see how to utilize an LLM Library in different use cases along with code build. The LLM library used is provided by Hugging Face, called Transformer Library.
Introducing the Transformer Library
The transformer package, provided by huggingface.io, tries to solve the various challenges we face in the NLP field. It provides pre-trained models, tokenizers, configs, various APIs, ready-made pipelines for our inference, etc.
It is a large language model (LLM) developed by Hugging Face and a community of over 1000 researchers. It is trained on a massive dataset of text and code, and it can generate text, translate languages, and answer questions. Here we are going to see the following application of the Transformer Library:
Sentiment Analysis
Named Entity Recognition
Text Generation
Translate language
Question Answering Pipeline
Summarization
Before jumping to the examples of Transformer Library, we need to install the library to use it.
Install the Transformer Library
pip install transformers
By using the pipeline feature of the Transformers Library, you can easily apply LLMs for text generation, question answering, sentiment analysis, named entity recognition, translation, and more.
from transformers import pipeline
Example: Question Answering Pipeline
To perform question-answering using the Transformers library, you can utilize the pipeline feature with a pre-trained question-answering model. Here’s an example:
from transformers import pipeline
# Define the list of file paths
file_paths = ['document1.txt', 'document2.txt', 'document3.txt']
# Read the contents of each file and store them in a list
documents = []
for file_path in file_paths:
with open(file_path, 'r') as file:
document = file.read()
documents.append(document)
# Concatenate the documents using a newline character
context = "\n".join(documents)
# Use the pipeline with the updated context
nlp = pipeline("question-answering")
result = nlp(question="When did Mars Mission Launched?", context=context)
print(result['answer'])
The code prints the below output correctly to the question – When did Mars Mission Launch?
Output - 5 November 2013
IBM’s AI chip mimics the human brain
The human brain can achieve remarkable performance while consuming little power. IBM’s new prototype chip works similarly to connections in human brains. Thus, it could make AI more energy efficient and less battery draining for devices like smartphones.
The chip is primarily analogue but also has digital elements, which makes it easier to put into existing AI systems.
It addresses the concerns raised about emissions from warehouses full of computers powering AI systems. It could also cut the water needed to cool power-hungry data centers.
Why does this matter?
The advancements suggest the emergence of brain-like chips in the near future. It would mean large and more complex AI workloads could be executed in low-power or battery-constrained environments, for example, cars, mobile phones, and cameras. It promises new and better AI applications with reduced costs.
NVIDIA’s tool to curate trillion-token datasets for pretraining LLMs
Most software/tools made to create massive datasets for training LLMs are not publicly released or scalable. This requires LLM developers to build their own tools to curate large language datasets. To meet this growing need, Nvidia has developed and released the NeMo Data Curator– a scalable data-curation tool that enables you to curate trillion-token multilingual datasets for pretraining LLMs. It can scale the following tasks to thousands of compute cores.
The tool curates high-quality data that leads to improved LLM downstream performance and will significantly benefit LLM developers attempting to build pretraining datasets.
Why does this matter?
Apart from improving model downstream performance with high-quality data, applying the above modules to your datasets helps reduce the burden of combing through unstructured data sources. Plus, it can potentially lead to greatly reduced pretraining costs, meaning relatively faster and cheaper development of AI applications.
Trustworthy LLMs: A survey and guideline for evaluating LLMs’ alignment
Ensuring alignment, which refers to making models behave in accordance with human intentions, has become a critical task before deploying LLMs in real-world applications. This new research has proposed a more fine-grained taxonomy of LLM alignment requirements. It not only helps practitioners unpack and understand the dimensions of alignments but also provides actionable guidelines for data collection efforts to develop desirable alignment processes.
It also thoroughly surveys the categories of LLMs that are likely to be crucial to improve their trustworthiness and shows how to build evaluation datasets for alignment accordingly.
Why does this matter?
The proposed framework facilitates a transparent, multi-objective evaluation of LLM trustworthiness. And it enables systematic iteration and deployment of LLMs. For instance, OpenAI has to devote six months to iteratively align GPT-4 before release. Thus, with clear and comprehensive guidance, it can facilitate faster time to market for AI applications that are safe, reliable, and aligned with human values.
Amazon’s push to match Microsoft and Google in generative AI LINK
Amazon is developing proprietary chips, named “Inferentia” and “Trainium,” to rival Nvidia GPUs in terms of training and speeding up generative AI models.
The company’s late entry into the generative AI market has put it in a position of catch-up, with competitors like Microsoft and Google already investing heavily and integrating AI models into their products.
Despite Amazon’s cloud dominance, it aims to differentiate by leveraging its custom silicon capabilities, with Trainium offering significant price-performance improvements, although Nvidia remains dominant for training models.
World first’s mass-produced humanoid robots with AI brains LINK
Chinese start-up Fourier Intelligence showcased its humanoid robot GR-1, capable of walking on two legs at 5km/h carrying a 50kg load, highlighting the potential of bipedal robots.
Fourier originally focused on rehabilitation robotics, but in 2019, it embarked on creating humanoid robots, with GR-1 achieving success after three years of development.
While challenges remain in commercializing humanoid robots, Fourier aims to mass-produce GR-1 by year-end and sees potential applications in elderly care, education, and more.
Microsoft Designer: An AI-powered Canva: a super cool product that I just found!
I just found out about Microsoft Designer, which is an AI-powered tool for creating all types of graphics, from logos to invitations to social media posts. If you like Canva, you should check this out.
Some cool features:
Prompt-to-design: From just a short description, Designer uses DALLE-2 to generate original and editable designs.
Brand-kit: stay on-brand by instantly applying your fonts and color pallets to any design; it an even suggest color combinations.
Other AI tools: suggests hashtags and captions; replace background of an image with your imagination; erase items from an image; auto-fill a section of the image with generated image.
OpenAI is reportedly in “financial trouble” due to the astronomical costs of running ChatGPT, which is losing $700,000 daily. The article states OpenAI may go bankrupt in 2024 but I disagree because of their investment from Microsoft totaling $10B… there’s no way they can spend all of that right? let me know in the comments.
Top talent being poached by rivals like Google and Meta.
GPU shortages hindering ability to train better models.
Increasing Competition
Cheaper open-source models can replace OpenAI’s APIs.
Musk’s xAI working on more right wing biased model.
Chinese firms buying up GPU stockpiles.
With ChatGPT’s massive costs outpacing revenue and problems like declining users and talent loss mounting, OpenAI seems to be in a precarious financial position as competition heats up.
Google appears to be readying new AI-powered tools for ChromeOS (Link)
Zoom rewrites policies to make clear user videos aren’t used to train AI (Link)
Anthropic raises $100M in funding from Korean telco giant SK Telecom (Link)
Modular, AI startup challenging Nvidia, discusses funding at $600M valuation (Link)
California turns to AI to spot wildfires, feeding on video from 1,000+ cameras (Link)
FEC to regulate AI deepfakes in political ads ahead of 2024 election (Link)
AI in Scientific Papers on August 14th, 2023
This research paper has found that LLMs can naturally read docs to learn how to use tools without any training. Instead of showing demonstration, just provide tool documentation. LLMs figured out how to use programs like image generators and video tracking software, without any new training [Link]
This paper analyses and visualises the political bias of major AI language models. ChatGPT and GPT-4 were most left-wing while Meta’s Llama was right-wing [Link]. This type of research is very important and highlights the inherent bias in these models. It’s practically impossible to remove bias also, and we don’t even know what they’ve been trained on. People need to understand, you control the models, you control what people see, especially as AI models are used more frequently and become mainstream
Remember the Westworld style paper with the 25 AI agents living their lives? It’s now open-source. It’s implications in gaming cannot be overstated. Can’t wait to see what comes of this [Link]
MetaGPT is framework using multiple agents to behave as an entire company – engineer, pm, architect etc. It has over 18k stars on github. This specialised for industries and companies will be powerful [Link]
This paper discusses reconstructing images from signals in the brain. Soon we’ll have brain interfaces that could read these signals consistently, maybe map everything you see? Potential is limitless [Link]
Nvidia is partnering with HuggingFace with DGX Cloud platform allowing people to train and tune AI models. They’re offering a “Training Cluster as a Service” which will help companies and individuals build and train models faster than ever [Link]
Stability AI has released their new AI LLM called StableCode. 16k context length and 3b params with other version on the way [Link]
This paper discusses a framework for designing and implementing complex interactions between AI systems called Flows [Link] Will be very important when building complex AI software in industry. Github will be uploaded soon [Link]
Nvidia announced that Adobe Firefly models will be available as APIs in Omniverse [Link] This thread breaks down what the Omniverse will look like [Link]
Anthropic CEO Dario Amodei thinks AI will reach educated levels of humans in 2-3 years [Link] For reference, Claude 2 is probably the second most powerful model alongside GPT4
Layerbrain is building AI agents that can be used across Stripe, Hubspot and slack using plain english [Link] Looks very cool
LLMs picking random numbers almost always pick the numbers 6-8 [Link]
Inflection founder Mustafa Suleyman says we’ll probably rely on LLMs more than the best trained and most experienced humans within 5 years [Link]. For context, Mustafa is one of the co founders of Google DeepMind – this guys knows AI
Writer, a startup using Nvidia’s NeMo discuss how it helped them build and scale over 10 models. NeMo isn’t publicly available but seems like a massive advantage considering Writer’s cloud infra, which is managed by 2 people, hosts a trillion API calls a month [Link] Link to NeMo [Link] Link to NeMo guardrails blog [Link]
Someone open-sourced smol-podcaster – it transcribes and labels speakers, formats the transcription, creates chapters with timestamps [Link]
Ultra realistic AI generated videos are coming. It’s impossible to tell they’re fake now [Link] Signup for early access here [Link]
Anthropic released Claude Instant 1.2. Its very fast, better at math and coding and hallucinates less [Link]
This guy released the code for his modded Google Nest Mini using OpenAI’s function calling to take notes and control his lights. Once Amazon & Apple integrates better LLMs into their prods, AI will truly be everywhere [Link]
If you search “As an AI language model” in Google Scholar a lot of papers come up… [Link]
OpenAI released custom instructions for ChatGPT free users, except for people in the US or UK [Link]
OpenAI, Google, Microsoft and Anthropic partnered with Darpa for their AI cyber challenge [Link]
PlayHT released their new text-to-voice ai model and it looks crazy good. Change the way its delivered by describing an emotion and much more [Link] [Link]
A paper by Google showcasing that AI models tend to repeat a user’s opinion back to them, even if its wrong. Thread breaking it down [Link] Link to paper [Link]
Medisearch comes out of YC and claims to have the best model for medical questions [Link]
Someone made a way to one-click install AudioLDM with gradio web ui [Link]
WizardLM released a new math model that outperforms ChatGPT on math skills [Link]
A team of researchers trained an AI model to hear the sounds of keystrokes and steal data. Apparently it has a 95% success rate. Link to article [Link] Link to paper [Link]
Yann LeCun gave a talk at MIT about Objective-Driven AI [Link]