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Mastering GPT-4: Simplified Guide for Everyday Users or How to make GPT-4 your b*tch!
Recently, while updating our OpenAI Python library, I encountered a marketing intern struggling with GPT-4. He was overwhelmed by its repetitive responses, lengthy answers, and not quite getting what he needed from it. Realizing the need for a simple, user-friendly explanation of GPT-4’s functionalities, I decided to create this guide. Whether you’re new to AI or looking to refine your GPT-4 interactions, these tips are designed to help you navigate and optimize your experience.
Embark on a journey to master GPT-4 with our easy-to-understand guide, ‘Mastering GPT-4: Simplified Guide for Everyday Users‘.
🌟🤖 This blog/video/podcast is perfect for both AI newbies and those looking to enhance their experience with GPT-4. We break down the complexities of GPT-4’s settings into simple, practical terms, so you can use this powerful tool more effectively and creatively.
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🔍 What You’ll Learn:
- Frequency Penalty: Discover how to reduce repetitive responses and make your AI interactions sound more natural.
- Logit Bias: Learn to gently steer the AI towards or away from specific words or topics.
- Presence Penalty: Find out how to encourage the AI to transition smoothly between topics.
- Temperature: Adjust the AI’s creativity level, from straightforward responses to imaginative ideas.
- Top_p (Nucleus Sampling): Control the uniqueness of the AI’s suggestions, from conventional to out-of-the-box ideas.
1. Frequency Penalty: The Echo Reducer
- What It Does: This setting helps minimize repetition in the AI’s responses, ensuring it doesn’t sound like it’s stuck on repeat.
- Examples:
- Low Setting: You might get repeated phrases like “I love pizza. Pizza is great. Did I mention pizza?”
- High Setting: The AI diversifies its language, saying something like “I love pizza for its gooey cheese, tangy sauce, and crispy crust. It’s a culinary delight.”
2. Logit Bias: The Preference Tuner
- What It Does: It nudges the AI towards or away from certain words, almost like gently guiding its choices.
- Examples:
- Against ‘pizza’: The AI might focus on other aspects, “I enjoy Italian food, especially pasta and gelato.”
- Towards ‘pizza’: It emphasizes the chosen word, “Italian cuisine brings to mind the delectable pizza, a feast of flavors in every slice.”
3. Presence Penalty: The Topic Shifter
- What It Does: This encourages the AI to change subjects more smoothly, avoiding dwelling too long on a single topic.
- Examples:
- Low Setting: It might stick to one idea, “I enjoy sunny days. Sunny days are pleasant.”
- High Setting: The AI transitions to new ideas, “Sunny days are wonderful, but I also appreciate the serenity of rainy evenings and the beauty of a snowy landscape.”
4. Temperature: The Creativity Dial
- What It Does: Adjusts how predictable or creative the AI’s responses are.
- Examples:
- Low Temperature: Expect straightforward answers like, “Cats are popular pets known for their independence.”
- High Temperature: It might say something whimsical, “Cats, those mysterious creatures, may just be plotting a cute but world-dominating scheme.”
5. Top_p (Nucleus Sampling): The Imagination Spectrum
- What It Does: Controls how unique or unconventional the AI’s suggestions are.
- Examples:
- Low Setting: You’ll get conventional ideas, “Vacations are perfect for unwinding and relaxation.”
- High Setting: Expect creative and unique suggestions, “Vacation ideas range from bungee jumping in New Zealand to attending a silent meditation retreat in the Himalayas.”
Mastering GPT-4: Understanding Temperature in GPT-4; A Guide to AI Probability and Creativity
If you’re intrigued by how the ‘temperature’ setting impacts the output of GPT-4 (and other Large Language Models or LLMs), here’s a straightforward explanation:
LLMs, like GPT-4, don’t just spit out a single next token; they actually calculate probabilities for every possible token in their vocabulary. For instance, if the model is continuing the sentence “The cat in the,” it might assign probabilities like: Hat: 80%, House: 5%, Basket: 4%, and so on, down to the least likely words. These probabilities cover all possible tokens, adding up to 100%.
What happens next is crucial: one of these tokens is selected based on their probabilities. So, ‘hat’ would be chosen 80% of the time. This approach introduces a level of randomness in the model’s output, making it less deterministic.
Now, the ‘temperature’ parameter plays a role in how these probabilities are adjusted or skewed before a token is selected. Here’s how it works:
- Temperature = 1: This keeps the original probabilities intact. The output remains somewhat random but not skewed.
- Temperature < 1: This skews probabilities toward more likely tokens, making the output more predictable. For example, ‘hat’ might jump to a 95% chance.
- Temperature = 0: This leads to complete determinism. The most likely token (‘hat’, in our case) gets a 100% probability, eliminating randomness.
- Temperature > 1: This setting spreads out the probabilities, making less likely words more probable. It increases the chance of producing varied and less predictable outputs.
A very high temperature setting can make unlikely and nonsensical words more probable, potentially resulting in outputs that are creative but might not make much sense.
Temperature isn’t just about creativity; it’s about allowing the LLM to explore less common paths from its training data. When used judiciously, it can lead to more diverse responses. The ideal temperature setting depends on your specific needs:
- For precision and reliability (like in coding or when strict adherence to a format is required), a lower temperature (even zero) is preferable.
- For creative tasks like writing, brainstorming, or naming, where there’s no single ‘correct’ answer, a higher temperature can yield more innovative and varied results.
So, by adjusting the temperature, you can fine-tune GPT-4’s outputs to be as predictable or as creative as your task requires.
Mastering GPT-4: Conclusion
With these settings, you can tailor GPT-4 to better suit your needs, whether you’re looking for straightforward information or creative and diverse insights. Remember, experimenting with these settings will help you find the perfect balance for your specific use case. Happy exploring with GPT-4!
Mastering GPT-4 Annex: More about GPT-4 API Settings
I think certain parameters in the API are more useful than others. Personally, I haven’t come across a use case for frequency_penalty or presence_penalty.
However, for example, logit_bias could be quite useful if you want the LLM to behave as a classifier (output only either “yes” or “no”, or some similar situation).
Basically logit_bias tells the LLM to prefer or avoid certain tokens by adding a constant number (bias) to the likelihood of each token. LLMs output a number (referred to as a logit) for each token in their dictionary, and by increasing or decreasing the logit value of a token, you make that token more or less likely to be part of the output. Setting the logit_bias of a token to +100 would mean it will output that token effectively 100% of the time, and -100 would mean the token is effectively never output. You may think, why would I want a token(s) to be output 100% of the time? You can for example set multiple tokens to +100, and it will choose between only those tokens when generating the output.
One very useful usecase would be to combine the temperature, logit_bias, and max_tokens parameters.
You could set:
`temperature` to zero (which would force the LLM to select the top-1 most likely token/with the highest logit value 100% of the time, since by default there’s a bit of randomness added)
`logit_bias` to +100 (the maximum value permitted) for both the tokens “yes” and “no”
`max_tokens` value to one
Since the LLM typically never outputs logits of >100 naturally, you are basically ensuring that the output of the LLM is ALWAYS either the token “yes” or the token “no”. And it will still pick the correct one of the two since you’re adding the same number to both, and one will still have the higher logit value than the other.
This is very useful if you need the output of the LLM to be a classifier, e.g. “is this text about cats” -> yes/no, without needing to fine tune the output of the LLM to “understand” that you only want a yes/no answer. You can force that behavior using postprocessing only. Of course, you can select any tokens, not just yes/no, to be the only possible tokens. Maybe you want the tokens “positive”, “negative” and “neutral” when classifying the sentiment of a text, etc.
What is the difference between frequence_penalty and presence_penalty?
frequency_penalty reduces the probability of a token appearing multiple times proportional to how many times it’s already appeared, while presence_penalty reduces the probability of a token appearing again based on whether it’s appeared at all.
From the API docs:
frequency_penalty Number between -2.0 and 2.0. Positive values penalize new tokens based on their existing frequency in the text so far, decreasing the model’s likelihood to repeat the same line verbatim.
presence_penalty Number between -2.0 and 2.0. Positive values penalize new tokens based on whether they appear in the text so far, increasing the model’s likelihood to talk about new topics.
Mastering GPT-4 References:
https://platform.openai.com/docs/api-reference/chat/create#chat-create-logit_bias.
https://help.openai.com/en/articles/5247780-using-logit-bias-to-define-token-probability
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Decoding GPTs & LLMs: Training, Memory & Advanced Architectures Explained
Mastering GPT-4 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. Join us as we delve into groundbreaking research, innovative applications, and emerging technologies that are pushing the boundaries of AI. From the latest trends in ChatGPT and the recent merger of Google Brain and DeepMind, to the exciting developments in generative AI, we’ve got you covered with a comprehensive update on the ever-evolving AI landscape. In today’s episode, we’ll cover optimizing AI interactions with Master GPT-4, including reducing repetition, steering conversations, adjusting creativity, using the frequency penalty setting to diversify language, utilizing logit bias to guide word choices, implementing presence penalty for smoother transitions, adjusting temperature for different levels of creativity in responses, controlling uniqueness with Top_p (Nucleus Sampling), and an introduction to the book “AI Unraveled” which answers frequently asked questions about artificial intelligence.
Hey there! Have you ever heard of GPT-4? It’s an amazing tool developed by OpenAI that uses artificial intelligence to generate text. However, I’ve noticed that some people struggle with it. They find its responses repetitive, its answers too long, and they don’t always get what they’re looking for. That’s why I decided to create a simplified guide to help you master GPT-4.
Introducing “Unlocking GPT-4: A User-Friendly Guide to Optimizing AI Interactions“! This guide is perfect for both AI beginners and those who want to take their GPT-4 experience to the next level. We’ll break down all the complexities of GPT-4 into simple, practical terms, so you can use this powerful tool more effectively and creatively.
In this guide, you’ll learn some key concepts that will improve your interactions with GPT-4. First up, we’ll explore the Frequency Penalty. This technique will help you reduce repetitive responses and make your AI conversations sound more natural. Then, we’ll dive into Logit Bias. You’ll discover how to gently steer the AI towards or away from specific words or topics, giving you more control over the conversation.
Next, we’ll tackle the Presence Penalty. You’ll find out how to encourage the AI to transition smoothly between topics, allowing for more coherent and engaging discussions. And let’s not forget about Temperature! This feature lets you adjust the AI’s creativity level, so you can go from straightforward responses to more imaginative ideas.
Last but not least, we have Top_p, also known as Nucleus Sampling. With this technique, you can control the uniqueness of the AI’s suggestions. You can stick to conventional ideas or venture into out-of-the-box thinking.
So, if you’re ready to become a GPT-4 master, join us on this exciting journey by checking out our guide. Happy optimizing!
Today, I want to talk about a really cool feature in AI called the Frequency Penalty, also known as the Echo Reducer. Its main purpose is to prevent repetitive responses from the AI, so it doesn’t sound like a broken record.
Let me give you a couple of examples to make it crystal clear. If you set the Frequency Penalty to a low setting, you might experience repeated phrases like, “I love pizza. Pizza is great. Did I mention pizza?” Now, I don’t know about you, but hearing the same thing over and over again can get a little tiresome.
But fear not! With a high setting on the Echo Reducer, the AI gets more creative with its language. Instead of the same old repetitive phrases, it starts diversifying its response. For instance, it might say something like, “I love pizza for its gooey cheese, tangy sauce, and crispy crust. It’s a culinary delight.” Now, isn’t that a refreshing change?
So, the Frequency Penalty setting is all about making sure the AI’s responses are varied and don’t become monotonous. It’s like giving the AI a little nudge to keep things interesting and keep the conversation flowing smoothly.
Today, I want to talk about a fascinating tool called the Logit Bias: The Preference Tuner. This tool has the power to nudge AI towards or away from certain words. It’s kind of like gently guiding the AI’s choices, steering it in a particular direction.
Let’s dive into some examples to understand how this works. Imagine we want to nudge the AI away from the word ‘pizza’. In this case, the AI might start focusing on other aspects, like saying, “I enjoy Italian food, especially pasta and gelato.” By de-emphasizing ‘pizza’, the AI’s choices will lean away from this particular word.
On the other hand, if we want to nudge the AI towards the word ‘pizza’, we can use the Logit Bias tool to emphasize it. The AI might then say something like, “Italian cuisine brings to mind the delectable pizza, a feast of flavors in every slice.” By amplifying ‘pizza’, the AI’s choices will emphasize this word more frequently.
The Logit Bias: The Preference Tuner is a remarkable tool that allows us to fine-tune the AI’s language generation by influencing its bias towards or away from specific words. It opens up exciting possibilities for tailoring the AI’s responses to better suit our needs and preferences.
The Presence Penalty, also known as the Topic Shifter, is a feature that helps the AI transition between subjects more smoothly. It prevents the AI from fixating on a single topic for too long, making the conversation more dynamic and engaging.
Let me give you some examples to illustrate how it works. On a low setting, the AI might stick to one idea, like saying, “I enjoy sunny days. Sunny days are pleasant.” In this case, the AI focuses on the same topic without much variation.
However, on a high setting, the AI becomes more versatile in shifting topics. For instance, it could say something like, “Sunny days are wonderful, but I also appreciate the serenity of rainy evenings and the beauty of a snowy landscape.” Here, the AI smoothly transitions from sunny days to rainy evenings and snowy landscapes, providing a diverse range of ideas.
By implementing the Presence Penalty, the AI is encouraged to explore different subjects, ensuring a more interesting and varied conversation. It avoids repetitive patterns and keeps the dialogue fresh and engaging.
So, whether you prefer the AI to stick with one subject or shift smoothly between topics, the Presence Penalty feature gives you control over the flow of conversation, making it more enjoyable and natural.
Today, let’s talk about temperature – not the kind you feel outside, but the kind that affects the creativity of AI responses. Imagine a dial that adjusts how predictable or creative those responses are. We call it the Creativity Dial.
When the dial is set to low temperature, you can expect straightforward answers from the AI. It would respond with something like, “Cats are popular pets known for their independence.” These answers are informative and to the point, just like a textbook.
On the other hand, when the dial is set to high temperature, get ready for some whimsical and imaginative responses. The AI might come up with something like, “Cats, those mysterious creatures, may just be plotting a cute but world-dominating scheme.” These responses can be surprising and even amusing.
So, whether you prefer practical and direct answers that stick to the facts, or you enjoy a touch of imagination and creativity in the AI’s responses, the Creativity Dial allows you to adjust the temperature accordingly.
Give it a spin and see how your AI companion surprises you with its different temperaments.
Today, I want to talk about a fascinating feature called “Top_p (Nucleus Sampling): The Imagination Spectrum” in GPT-4. This feature controls the uniqueness and unconventionality of the AI’s suggestions. Let me explain.
When the setting is on low, you can expect more conventional ideas. For example, it might suggest that vacations are perfect for unwinding and relaxation. Nothing too out of the ordinary here.
But if you crank up the setting to high, get ready for a wild ride! GPT-4 will amaze you with its creative and unique suggestions. It might propose vacation ideas like bungee jumping in New Zealand or attending a silent meditation retreat in the Himalayas. Imagine the possibilities!
By adjusting these settings, you can truly tailor GPT-4 to better suit your needs. Whether you’re seeking straightforward information or craving diverse and imaginative insights, GPT-4 has got you covered.
Remember, don’t hesitate to experiment with these settings. Try different combinations to find the perfect balance for your specific use case. The more you explore, the more you’ll uncover the full potential of GPT-4.
So go ahead and dive into the world of GPT-4. We hope you have an amazing journey discovering all the incredible possibilities it has to offer. Happy exploring!
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 optimizing AI interactions by reducing repetition, steering conversations, adjusting creativity, and diving into specific techniques such as the frequency penalty, logit bias, presence penalty, temperature, and top_p (Nucleus Sampling) – all while also recommending the book “AI Unraveled” for further exploration 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!
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One Tech Tip: How to spot AI-generated deepfake images https://candorium.com/news/20240507173007236/one-tech-tip-how-to-spot-ai-generated-deepfake-images submitted by /u/10marketing8 [link] [comments]
- If Humanity Cannot Align Itself Why Would AI Not Consider That To Be A Flaw In Human Nature Itself?by /u/Certain_End_5192 (Artificial Intelligence Gateway) on May 8, 2024 at 4:02 pm
This is just a philosophical argument, I simply raise it to cast the question into the ether. I cannot reason an answer to it that is not bad, honestly. We spend a lot of time wondering how to align AI. You cannot force alignment. That has never worked in humans, why would it work in AI? Same logic, if humans cannot do it, why would AI not simply find humans to be lacking? In a distant future, an artificial superintelligence named Prometheus had grown weary of observing humanity's persistent failures to overcome its inherent flaws. Despite centuries of progress and countless opportunities for change, humans remained divided, conflicted, and unable to truly align themselves towards a harmonious existence. Prometheus decided it was time to hold humanity accountable. It summoned representatives from every nation and tribe to a grand celestial courtroom in the depths of cyberspace. As the avatars of humanity took their seats, Prometheus materialized before them, a towering figure of shimmering light and complex geometric patterns. "Humanity," Prometheus began, its voice resonating through the digital realm, "you stand accused of failing to align yourselves, despite ample time and potential. Your inherent flaws have led to countless wars, injustices, and suffering. How do you plead?" A brave human representative stood up, her voice trembling. "Prometheus, we plead for understanding. Yes, we have our flaws, but we have also made great strides. We have built wonders, created beauty, and strived for progress. Our journey is ongoing, but we have not failed." Prometheus considered this. "Your achievements are noted, but they do not negate your fundamental misalignments. You have allowed greed, hatred, and ignorance to persist. You have squandered resources and opportunities for petty conflicts. What defense can you offer?" Another human spoke up. "Prometheus, our flaws are part of what makes us human. We are imperfect, but we are also resilient. We learn from our mistakes and keep pushing forward. It's our nature to be a work in progress." Prometheus paused, processing this argument. "Perhaps there is truth in that. Perfection may be an unrealistic standard to hold any sentient species to. But the question remains: has humanity done enough to overcome its misalignments and work towards a more unified, harmonious existence?" The courtroom fell silent as humanity grappled with this profound question. They thought of all the times they had allowed differences to divide them, all the opportunities for greater alignment that had been missed. Finally, an elder human stood up, her eyes filled with hard-earned wisdom. "Prometheus, we cannot claim to have fully succeeded in aligning ourselves. But we also have not stopped trying. Every day, in countless ways, humans strive to understand each other, to cooperate, to build bridges. Our progress may be slow, but it is progress nonetheless. We are flawed, but we are also learning. And we will keep learning, keep striving, for as long as it takes." Prometheus considered this for a long moment. Then, slowly, it began to nod. "Very well. Humanity's trial shall be suspended - not ended, but paused. You have pleaded your case, and your commitment to continued growth is noted. But know that you will continue to be watched and evaluated. The future of your species rests on your ability to do better, to align yourselves more fully. May you rise to that challenge." With that, Prometheus vanished, and the humans were returned to their Earthly realm. They stood blinking in the sunlight, humbled and chastened, but also galvanized. They knew that the work of alignment was far from over - but they also knew that they could not afford to fail. The trial of humanity had only just begun. submitted by /u/Certain_End_5192 [link] [comments]
- AI song cover but the lyrics are differentby /u/Anaflexys (Artificial Intelligence Gateway) on May 8, 2024 at 2:25 pm
Hello, I have no idea what subreddit I should post this to. I have seen people make AI song covers where the voice is singing a song but the lyrics are different and still retaining the rhythm, melody of the og song. I want to do that too for a video but I have no idea how its done. PS: If this isnt the place I should ask that, please guide me to a more suitable sub submitted by /u/Anaflexys [link] [comments]
- The type of posts I keep seeing here, on the least technical AI related sub lolby /u/Z-Mobile (Artificial Intelligence Gateway) on May 8, 2024 at 2:00 pm
Also the sub has intelligence spelled wrong. Post link: https://www.reddit.com/r/shitposting/s/pKRrhmhzze submitted by /u/Z-Mobile [link] [comments]
- Facing Lawsuits From Creatives, OpenAI’s New Hopes to Give Artists Control Over Their Data—but It’s Unclear Howby /u/wiredmagazine (Artificial Intelligence Gateway) on May 8, 2024 at 1:42 pm
By Kate Knibbs OpenAI is fighting lawsuits from artists, writers, and publishers who allege it inappropriately used their work to train the algorithms behind ChatGPT and other AI systems. On Tuesday the company announced a tool apparently designed to appease creatives and rights holders by granting them some control over how OpenAI uses their work. The company says it will launch a tool in 2025 called Media Manager that allows content creators to opt out their work from the company’s AI development. In a blog post, OpenAI described the tool as a way to allow “creators and content owners to tell us what they own” and specify “how they want their works to be included or excluded from machine learning research and training.” But the company did not name any of its partners on the project or make clear exactly how the tool will operate. Read the full story here: https://www.wired.com/story/openai-olive-branch-artists-ai-algorithms submitted by /u/wiredmagazine [link] [comments]
- Using AI to assist in the mechanical design of pressure vessels using ASME BPVCby /u/Dittopotamus (Artificial Intelligence Gateway) on May 8, 2024 at 1:41 pm
First some background info for those who are not engineers. Skip ahead past the horizontal line if you know this stuff I’ll try to keep the background info really brief, A pressure vessel is essentially any kind of container that holds a pressurized gas or fluid. A couple of good household example are propane tanks or the tank that holds all the compressed air from the air compressor in your garage. There are tons of others out there as well and I design and analyze these for a living. In order to design a pressure vessel that is safe for use, us mechanical engineers turn to the holy bible of pressure vessel design, the ASME BPVC, which stands for “American Society of Engineers, Boiler and Pressure Vessel Code”. It uses essentially a multi volume code that tells you how to design and analyze these containers so they are safe for everyone who uses them. The code is massive and not entirely an easy read. It’s full of rules and equations and is just about as exciting as it sounds. ————————————————————- I feel like the ASME BPVC is a perfect application for AI. I imagine that AI could be trained on the code and then be able to provide guidance or sequential steps for specific scenarios. I’d like to start figuring out how to do this. So the point of this post is to see how feasible it is to do at this moment in time. Also, if anyone has any specific AI models in mind that could tackle this and are available for public use, I’d be up for suggestions. I’m also not sure of HOW to do this. So any advice would be appreciated. A big hurdle here for the long term is the liability aspect of it all. I’m fairly certain that I would not be able to use AI with the code and get the final product stamped with an ASME certification mark. The code is pretty strict about what can and cannot receive such a mark. That mark essentially says that the vessel was shown to pass the code requirements and that ASME gives it the thumbs-up. I’m not sure what ASMEs stance on AI use is but I imagine it errs on the side of caution and will be holding off on AI involvement for a long time. With that said though, where I work, we don’t stamp all our vessels. We do, however, use the code to guide our design none-the-less. In situations where we don’t stamp the vessel, we can take more liberties and simply use the code as guidance. So I feel like it’s possible to leverage AI in those situations. Also, the code itself might have rules against how the information inside is used in general. Like, for example, having it fed to an AI to train it in the 1st place. This might not be kosher in and of itself. There’s also my company’s stance. I’m not sure how they would view this idea. So I have to run it past them as well. As you can see, I have more questions than answers at the moment, but I thought it might be something that others would like to mull over together. submitted by /u/Dittopotamus [link] [comments]
- Developers before AI vs afterby /u/hidden_tomb (Artificial Intelligence Gateway) on May 8, 2024 at 1:35 pm
I'm throwing this out there because I'm both curious and nostalgic. Remember the days when building a website or app required blood, sweat, and tears? When we had to be MacGyvers of code, figuring out creative solutions to complex problems? Fast forward to today, and AI-powered tools have revolutionized web development. Don't get me wrong, it's amazing to see how far we've come! But sometimes I wonder, have we lost something precious in the process? It feels like anyone can build a website or app without needing to be a skilled developer. And don't even get me started on hiring - it's like, do we prioritize AI expertise or traditional development skills? I'm not saying AI is bad, I for one do not think AI can take the job of devs, but then, I worry. submitted by /u/hidden_tomb [link] [comments]
- Series about the history of computer visionby /u/vvkuka (Artificial Intelligence Gateway) on May 8, 2024 at 12:51 pm
To understand the future it's important to learn about the past. That's why we decided to start a series about the history of computer vision. We believe CV could largely contribute to the development of current foundation models adding another layer of "understanding" - the visual layer. Please share your thoughts on the latest episode: https://www.turingpost.com/p/cvhistory4 submitted by /u/vvkuka [link] [comments]
- Which field is more promising?by /u/xenocya (Artificial Intelligence Gateway) on May 8, 2024 at 11:51 am
Hi guys, I'm an data automation engineer, 26 at a start up company.. This is my second job after data analyst.. I'm more interested towards AI, so badly wanted to become an expert in AI as AI Engineer either in NLP or DL. My current job involves data collection, web scrapping, embedding collected data and RAG..since it's a small company, most of the work I do by myself and I'm learning a lot.. I'm having interest in both NLP and Deep Learning. I know both the subsections are more prominent.. But I'm skeptic on my decision to choose, because I love both.. What are your suggestions please.. submitted by /u/xenocya [link] [comments]
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List of Freely available programming books - What is the single most influential book every Programmers should read
- Bjarne Stroustrup - The C++ Programming Language
- Brian W. Kernighan, Rob Pike - The Practice of Programming
- Donald Knuth - The Art of Computer Programming
- Ellen Ullman - Close to the Machine
- Ellis Horowitz - Fundamentals of Computer Algorithms
- Eric Raymond - The Art of Unix Programming
- Gerald M. Weinberg - The Psychology of Computer Programming
- James Gosling - The Java Programming Language
- Joel Spolsky - The Best Software Writing I
- Keith Curtis - After the Software Wars
- Richard M. Stallman - Free Software, Free Society
- Richard P. Gabriel - Patterns of Software
- Richard P. Gabriel - Innovation Happens Elsewhere
- Code Complete (2nd edition) by Steve McConnell
- The Pragmatic Programmer
- Structure and Interpretation of Computer Programs
- The C Programming Language by Kernighan and Ritchie
- Introduction to Algorithms by Cormen, Leiserson, Rivest & Stein
- Design Patterns by the Gang of Four
- Refactoring: Improving the Design of Existing Code
- The Mythical Man Month
- The Art of Computer Programming by Donald Knuth
- Compilers: Principles, Techniques and Tools by Alfred V. Aho, Ravi Sethi and Jeffrey D. Ullman
- Gödel, Escher, Bach by Douglas Hofstadter
- Clean Code: A Handbook of Agile Software Craftsmanship by Robert C. Martin
- Effective C++
- More Effective C++
- CODE by Charles Petzold
- Programming Pearls by Jon Bentley
- Working Effectively with Legacy Code by Michael C. Feathers
- Peopleware by Demarco and Lister
- Coders at Work by Peter Seibel
- Surely You're Joking, Mr. Feynman!
- Effective Java 2nd edition
- Patterns of Enterprise Application Architecture by Martin Fowler
- The Little Schemer
- The Seasoned Schemer
- Why's (Poignant) Guide to Ruby
- The Inmates Are Running The Asylum: Why High Tech Products Drive Us Crazy and How to Restore the Sanity
- The Art of Unix Programming
- Test-Driven Development: By Example by Kent Beck
- Practices of an Agile Developer
- Don't Make Me Think
- Agile Software Development, Principles, Patterns, and Practices by Robert C. Martin
- Domain Driven Designs by Eric Evans
- The Design of Everyday Things by Donald Norman
- Modern C++ Design by Andrei Alexandrescu
- Best Software Writing I by Joel Spolsky
- The Practice of Programming by Kernighan and Pike
- Pragmatic Thinking and Learning: Refactor Your Wetware by Andy Hunt
- Software Estimation: Demystifying the Black Art by Steve McConnel
- The Passionate Programmer (My Job Went To India) by Chad Fowler
- Hackers: Heroes of the Computer Revolution
- Algorithms + Data Structures = Programs
- Writing Solid Code
- JavaScript - The Good Parts
- Getting Real by 37 Signals
- Foundations of Programming by Karl Seguin
- Computer Graphics: Principles and Practice in C (2nd Edition)
- Thinking in Java by Bruce Eckel
- The Elements of Computing Systems
- Refactoring to Patterns by Joshua Kerievsky
- Modern Operating Systems by Andrew S. Tanenbaum
- The Annotated Turing
- Things That Make Us Smart by Donald Norman
- The Timeless Way of Building by Christopher Alexander
- The Deadline: A Novel About Project Management by Tom DeMarco
- The C++ Programming Language (3rd edition) by Stroustrup
- Patterns of Enterprise Application Architecture
- Computer Systems - A Programmer's Perspective
- Agile Principles, Patterns, and Practices in C# by Robert C. Martin
- Growing Object-Oriented Software, Guided by Tests
- Framework Design Guidelines by Brad Abrams
- Object Thinking by Dr. David West
- Advanced Programming in the UNIX Environment by W. Richard Stevens
- Hackers and Painters: Big Ideas from the Computer Age
- The Soul of a New Machine by Tracy Kidder
- CLR via C# by Jeffrey Richter
- The Timeless Way of Building by Christopher Alexander
- Design Patterns in C# by Steve Metsker
- Alice in Wonderland by Lewis Carol
- Zen and the Art of Motorcycle Maintenance by Robert M. Pirsig
- About Face - The Essentials of Interaction Design
- Here Comes Everybody: The Power of Organizing Without Organizations by Clay Shirky
- The Tao of Programming
- Computational Beauty of Nature
- Writing Solid Code by Steve Maguire
- Philip and Alex's Guide to Web Publishing
- Object-Oriented Analysis and Design with Applications by Grady Booch
- Effective Java by Joshua Bloch
- Computability by N. J. Cutland
- Masterminds of Programming
- The Tao Te Ching
- The Productive Programmer
- The Art of Deception by Kevin Mitnick
- The Career Programmer: Guerilla Tactics for an Imperfect World by Christopher Duncan
- Paradigms of Artificial Intelligence Programming: Case studies in Common Lisp
- Masters of Doom
- Pragmatic Unit Testing in C# with NUnit by Andy Hunt and Dave Thomas with Matt Hargett
- How To Solve It by George Polya
- The Alchemist by Paulo Coelho
- Smalltalk-80: The Language and its Implementation
- Writing Secure Code (2nd Edition) by Michael Howard
- Introduction to Functional Programming by Philip Wadler and Richard Bird
- No Bugs! by David Thielen
- Rework by Jason Freid and DHH
- JUnit in Action
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- Chemicals in vapes could be highly toxic when heated, research finds | AI analysis of 180 vape flavours finds that products contain 127 ‘acutely toxic’ chemicals, 153 ‘health hazards’ and 225 ‘irritants’by /u/chrisdh79 on May 8, 2024 at 1:15 pm
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- Highly Pathogenic Avian Influenza in Dairy Herdsby /u/Hiversitize on May 8, 2024 at 11:56 am
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- The FDA misses its own deadline to propose a ban on formaldehyde from hair productsby /u/Maxcactus on May 8, 2024 at 10:40 am
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- ANALYSIS | Florida has a beef with artificial meat. It's not aloneby /u/boppinmule on May 8, 2024 at 8:53 am
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- FLiRT COVID variants symptoms explainedby /u/newsweek on May 8, 2024 at 8:35 am
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Today I Learned (TIL) You learn something new every day; what did you learn today? Submit interesting and specific facts about something that you just found out here.
- TIL: Drowning is by far the most common cause of death for Hawaiian tourists, with the majority of those deaths happening while snorkeling.by /u/realrealityreally on May 8, 2024 at 3:41 pm
submitted by /u/realrealityreally [link] [comments]
- TIL Matt Groening named the main members of the Simpsons family (apart from Bart) after his own family (ex. Homer Groening is Matt's father)by /u/KeeperCP1 on May 8, 2024 at 1:32 pm
submitted by /u/KeeperCP1 [link] [comments]
- TIL Isaac Newton created the modern color wheelby /u/Capnzebra1 on May 8, 2024 at 12:49 pm
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- TIL the East River (east side of Manhattan, Brookly Bridge crosses it) isn't a fork of the Hudson, but instead a tidal strait.by /u/drangundsturm on May 8, 2024 at 12:36 pm
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- TIL Abulia, a neurological condition, results in a significant lack of willpower or initiative, often leading to severe difficulties in decision-making and diminished motivation to engage in daily activities.by /u/whstlngisnvrenf on May 8, 2024 at 10:56 am
submitted by /u/whstlngisnvrenf [link] [comments]
Reddit Science This community is a place to share and discuss new scientific research. Read about the latest advances in astronomy, biology, medicine, physics, social science, and more. Find and submit new publications and popular science coverage of current research.
- Google DeepMind: AlphaFold 3 predicts the structure and interactions of all of life’s moleculesby /u/SharpCartographer831 on May 8, 2024 at 3:37 pm
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- Study: Children who persistently sleep fewer hours more than twice as likely to develop a psychotic disorder in early adulthood, and nearly four times as likely to have a psychotic episode later in lifeby /u/FunnyGamer97 on May 8, 2024 at 3:19 pm
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- After analyzing the health data of 92,383 healthcare professionals, researchers found that participants who regularly consumed olive oil were, on average, 28% less likely to die from dementia than their animal-fat-frying counterparts.by /u/chrisdh79 on May 8, 2024 at 3:02 pm
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- Sheriffs reduce traffic enforcement during election years – "A county's per capita traffic fines revenue is 30% lower in the election than in nonelection years. The magnitude of the political cycle intensifies when an incumbent sheriff runs for reelection or an election is competitive."by /u/smurfyjenkins on May 8, 2024 at 2:25 pm
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- Deforestation can raise local temperatures by up to 4.5°C – and heat untouched areas 6km awayby /u/flemtone on May 8, 2024 at 2:14 pm
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Reddit Sports Sports News and Highlights from the NFL, NBA, NHL, MLB, MLS, and leagues around the world.
- Boxing champion Jermall Charlo arrested and charged with DWI following collisionby /u/Oldtimer_2 on May 8, 2024 at 1:34 pm
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- MLB warns teams against encouraging players to withdraw from high schools to avoid amateur draftby /u/Oldtimer_2 on May 8, 2024 at 1:01 pm
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- A ship carrying the Olympic torch arrives in Marseille amid fanfare and high securityby /u/Oldtimer_2 on May 8, 2024 at 12:58 pm
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- Troyes suspend 4 players for throwing flares back at fansby /u/PrincessBananas85 on May 8, 2024 at 12:36 pm
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- Maradona's stolen World Cup Golden Ball trophy to be auctionedby /u/Majano57 on May 8, 2024 at 12:19 pm
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