Tag: AI in Daily Life

The Future of Generative AI: From Art to Reality Shaping.

Explore the transformative potential of generative AI in our latest AI Unraveled episode. From AI-driven entertainment to reality-altering technologies, we delve deep into what the future holds.

This episode covers how generative AI could revolutionize movie making, impact creative professions, and even extend to DNA alteration. We also discuss its integration in technology over the next decade, from smartphones to fully immersive VR worlds.”

Listen to the Future of Generative AI here

#GenerativeAI #AIUnraveled #AIFuture

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 generative AI in entertainment, the potential transformation of creative jobs, DNA alteration and physical enhancements, personalized solutions and their ethical implications, AI integration in various areas, the future integration of AI in daily life, key points from the episode, and a recommendation for the book “AI Unraveled” to better understand artificial intelligence.

The Future of Generative AI: The Evolution of Generative AI in Entertainment

Hey there! Today we’re diving into the fascinating world of generative AI in entertainment. Picture this: a Netflix powered by generative AI where movies are actually created based on prompts. It’s like having an AI scriptwriter and director all in one!

Imagine how this could revolutionize the way we approach scriptwriting and audio-visual content creation. With generative AI, we could have an endless stream of unique and personalized movies tailor-made to our interests. No more scrolling through endless options trying to find something we like – the AI knows exactly what we’re into and delivers a movie that hits all the right notes.

But, of course, this innovation isn’t without its challenges and ethical considerations. While generative AI offers immense potential, we must be mindful of the biases it may inadvertently introduce into the content it creates. We don’t want movies that perpetuate harmful stereotypes or discriminatory narratives. Striking the right balance between creativity and responsibility is crucial.

Additionally, there’s the question of copyright and ownership. Who would own the rights to a movie created by a generative AI? Would it be the platform, the AI, or the person who originally provided the prompt? This raises a whole new set of legal and ethical questions that need to be addressed.

Overall, generative AI has the power to transform our entertainment landscape. However, we must tread carefully, ensuring that the benefits outweigh the potential pitfalls. Exciting times lie ahead in the world of AI-driven entertainment!

The Future of Generative AI: The Impact on Creative Professions

In this segment, let’s talk about how AI advancements are impacting creative professions. As a graphic designer myself, I have some personal concerns about the need to adapt to these advancements. It’s important for us to understand how generative AI might transform jobs in creative fields.

AI is becoming increasingly capable of producing creative content such as music, art, and even writing. This has raised concerns among many creatives, including myself, about the future of our profession. Will AI eventually replace us? While it’s too early to say for sure, it’s important to recognize that AI is more of a tool to enhance our abilities rather than a complete replacement.

Generative AI, for example, can help automate certain repetitive tasks, freeing up our time to focus on more complex and creative work. This can be seen as an opportunity to upskill and expand our expertise. By embracing AI and learning to work alongside it, we can adapt to the changing landscape of creative professions.

Upskilling is crucial in this evolving industry. It’s important to stay updated with the latest AI technologies and learn how to leverage them in our work. By doing so, we can stay one step ahead and continue to thrive in our creative careers.

Overall, while AI advancements may bring some challenges, they also present us with opportunities to grow and innovate. By being open-minded, adaptable, and willing to learn, we can navigate these changes and continue to excel in our creative professions.

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The Future of Generative AI: Beyond Content Generation – The Realm of Physical Alterations

Today, folks, we’re diving into the captivating world of physical alterations. You see, there’s more to AI than just creating content. It’s time to explore how AI can take a leap into the realm of altering our DNA and advancing medical applications.

Imagine this: using AI to enhance our physical selves. Picture people with wings or scales. Sounds pretty crazy, right? Well, it might not be as far-fetched as you think. With generative AI, we have the potential to take our bodies to the next level. We’re talking about truly transforming ourselves, pushing the boundaries of what it means to be human.

But let’s not forget to consider the ethical and societal implications. As exciting as these advancements may be, there are some serious questions to ponder. Are we playing God? Will these enhancements create a divide between those who can afford them and those who cannot? How will these alterations affect our sense of identity and equality?

It’s a complex debate, my friends, one that raises profound moral and philosophical questions. On one hand, we have the potential for incredible medical breakthroughs and physical advancements. On the other hand, we risk stepping into dangerous territory, compromising our values and creating a divide in society.

So, as we venture further into the realm of physical alterations, let’s keep our eyes wide open and our minds even wider. There’s a lot at stake here, and it’s up to us to navigate the uncharted waters of AI and its impact on our very existence.

Generative AI as Personalized Technology Tools

In this segment, let’s dive into the exciting world of generative AI and how it can revolutionize personalized technology tools. Picture this: AI algorithms evolving so rapidly that they can create customized solutions tailored specifically to individual needs! It’s mind-boggling, isn’t it?

Now, let’s draw a comparison to “Clarke tech,” where technology appears almost magical. Just like in Arthur C. Clarke’s famous quote, “Any sufficiently advanced technology is indistinguishable from magic.” Generative AI has the potential to bring that kind of magic to our lives by creating seemingly miraculous solutions.

One of the key advantages of generative AI is its ability to understand context. This means that AI systems can comprehend the nuances and subtleties of our queries, allowing them to provide highly personalized and relevant responses. Imagine having a chatbot that not only recognizes what you’re saying but truly understands it in context, leading to more accurate and helpful interactions.

The future of generative AI holds immense promise for creating personalized experiences. As it continues to evolve, we can look forward to technology that adapts itself to our unique needs and preferences. It’s an exciting time to be alive, as we witness the merging of cutting-edge AI advancements and the practicality of personalized technology tools. So, brace yourselves for a future where technology becomes not just intelligent, but intelligently tailored to each and every one of us.

Generative AI in Everyday Technology (1-3 Year Predictions)

So, let’s talk about what’s in store for AI in the near future. We’re looking at a world where AI will become a standard feature in our smartphones, social media platforms, and even education. It’s like having a personal assistant right at our fingertips.

One interesting trend that we’re seeing is the blurring lines between AI-generated and traditional art. This opens up exciting possibilities for artists and enthusiasts alike. AI algorithms can now analyze artistic styles and create their own unique pieces, which can sometimes be hard to distinguish from those made by human hands. It’s kind of mind-blowing when you think about it.

Another aspect to consider is the potential ubiquity of AI in content creation tools. We’re already witnessing the power of AI in assisting with tasks like video editing and graphic design. But in the not too distant future, we may reach a point where AI is an integral part of every creative process. From writing articles to composing music, AI could become an indispensable tool. It’ll be interesting to see how this plays out and how creatives in different fields embrace it.

All in all, AI integration in everyday technology is set to redefine the way we interact with our devices and the world around us. The lines between human and machine are definitely starting to blur. It’s an exciting time to witness these innovations unfold.

So picture this – a future where artificial intelligence is seamlessly woven into every aspect of our lives. We’re talking about a world where AI is a part of our daily routine, be it for fun and games or even the most mundane of tasks like operating appliances.

But let’s take it up a notch. Imagine fully immersive virtual reality worlds that are not just created by AI, but also have AI-generated narratives. We’re not just talking about strapping on a VR headset and stepping into a pre-designed world. We’re talking about AI crafting dynamic storylines within these virtual realms, giving us an unprecedented level of interactivity and immersion.

Now, to make all this glorious future-tech a reality, we need to consider the advancements in material sciences and computing that will be crucial. We’re talking about breakthroughs that will power these AI-driven VR worlds, allowing them to run flawlessly with immense processing power. We’re talking about materials that enable lightweight, comfortable VR headsets that we can wear for hours on end.

It’s mind-boggling to think about the possibilities that this integration of AI, VR, and material sciences holds for our future. We’re talking about a world where reality and virtuality blend seamlessly, and where our interactions with technology become more natural and fluid than ever before. And it’s not a distant future either – this could become a reality in just the next decade.

The Future of Generative AI: Long-Term Predictions and Societal Integration (10 Years)

So hold on tight, because the future is only getting more exciting from here!

So, here’s the deal. We’ve covered a lot in this episode, and it’s time to sum it all up. We’ve discussed some key points when it comes to generative AI and how it has the power to reshape our world. From creating realistic deepfake videos to generating lifelike voices and even designing unique artwork, the possibilities are truly mind-boggling.

But let’s not forget about the potential ethical concerns. With this technology advancing at such a rapid pace, we must be cautious about the misuse and manipulation that could occur. It’s important for us to have regulations and guidelines in place to ensure that generative AI is used responsibly.

Now, I want to hear from you, our listeners! What are your thoughts on the future of generative AI? Do you think it will bring positive changes or cause more harm than good? And what about your predictions? Where do you see this technology heading in the next decade?

Remember, your voice matters, and we’d love to hear your insights on this topic. So don’t be shy, reach out to us and share your thoughts. Together, let’s unravel the potential of generative AI and shape our future responsibly.

Oh, if you’re looking to dive deeper into the fascinating world of artificial intelligence, I’ve got just the thing for you! There’s a fantastic book called “AI Unraveled: Demystifying Frequently Asked Questions on Artificial Intelligence” that you absolutely have to check out. Trust me, it’s a game-changer.

What’s great about this book is that it’s the ultimate guide to understanding artificial intelligence. It takes those complex concepts and breaks them down into digestible pieces, answering all those burning questions you might have. No more scratching your head in confusion!

Now, the best part is that it’s super accessible. You can grab a copy of “AI Unraveled” from popular platforms like Shopify, Apple, Google, or Amazon. Just take your pick, and you’ll be on your way to unraveling the mysteries of AI!

So, if you’re eager to expand your knowledge and get a better grasp on artificial intelligence, don’t miss out on “AI Unraveled.” It’s the must-have book that’s sure to satisfy your curiosity. Happy reading!

The Future of Generative AI: Conclusion

In this episode, we uncovered the groundbreaking potential of generative AI in entertainment, creative jobs, DNA alteration, personalized solutions, AI integration in daily life, and more, while also exploring the ethical implications – don’t forget to grab your copy of “AI Unraveled” for a deeper understanding! 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!

📢 Advertise with us and Sponsorship Opportunities

Are you eager to expand your understanding of artificial intelligence? Look no further than the essential book “AI Unraveled: Demystifying Frequently Asked Questions on Artificial Intelligence,” available at Shopify, Apple, Google, or Amazon

Elevate Your Design Game with Photoshop’s Generative Fill

Take your creative projects to the next level with #Photoshop’s Generative Fill! This AI-powered tool is a game-changer for designers and artists.

Tutorial: How to Use generative Fill

➡ Use any selection tool to highlight an area or object in your image. Click the Generative Fill button in the Contextual Task Bar.

➡ Enter a prompt describing your vision in the text-entry box. Or, leave it blank and let Photoshop auto-fill the area based on the surroundings.

➡ Click ‘Generate’. Be amazed by the thumbnail previews of variations tailored to your prompt. Each option is added as a Generative Layer in your Layers panel, keeping your original image intact.

Pro Tip: To generate even more options, click Generate again. You can also try editing your prompt to fine-tune your results. Dream it, type it, see it

https://youtube.com/shorts/i1fLaYd4Qnk

A Daily Chronicle of AI Innovations in November 2023

• Adaptable and Intelligent Generative AI through Advanced Information Lifecycle (AIL)
  by /u/siphonfilter79 (Artificial Intelligence) on May 9, 2024 at 1:07 am

  Video: Husky AI: An Ensemble Learning Architecture for Dynamic Context-Aware Retrieval and Generation (youtube.com) Pleases excuse my video, I will make a improved one. I would like to do a live event. Abstract: Husky AI represents a groundbreaking advancement in generative AI, leveraging the power of Advanced Information Lifecycle (AIL) management to achieve unparalleled adaptability, accuracy, and context-aware intelligence. This paper delves into the core components of Husky AI's architecture, showcasing how AIL enables intelligent data manipulation, dynamic knowledge evolution, and iterative learning. By integrating the innovative classes developed entirely in python, using open source tools , Husky AI dynamically incorporates real-time data from the web and its local ElasticSearchDocument DB, significantly expanding its knowledge base and contextual understanding. The system's ability to continuously learn and refine its response generation capabilities through user interactions sets a new standard in the development of generative AI systems. Husky AI's superior performance, real-time knowledge integration, and generalizability across applications position it as a paradigm shift in the field, paving the way for the future of intelligent systems. Husky AI Architecture: A Symphony of AIL Components At the heart of Husky AI's success lies its innovative architecture, which seamlessly integrates various AIL components to achieve its cutting-edge capabilities. Let's dive into the core elements that make Husky AI a game-changer: 2.1. Intelligent Data Manipulation: Streamlining Information Processing Husky AI's foundation is built upon intelligent data manipulation techniques that ensure efficient storage, retrieval, and processing of information. The system employs state-of-the-art sentence transformers to convert unstructured textual data into dense vector representations, known as embeddings. These embeddings capture the semantic meaning and relationships within the data, enabling precise similarity searches during information retrieval. Under the hood, the preprocess_and_write_data function works its magic. It ingests raw data, encodes it as a text string, and feeds it to the sentence transformer model. The resulting embeddings are then stored alongside the data within a Document object, which is subsequently committed to the document store for efficient retrieval. 2.2. Dynamic Context-Aware Retrieval: The Mastermind of Relevance Husky AI takes information retrieval to the next level with its dynamic context-aware retrieval mechanism. The MultiModalRetriever class, in seamless integration with Elasticsearch (ESDB), serves as the mastermind behind this operation, ensuring lightning-fast indexing and retrieval. When a user query arrives, the MultiModalRetriever springs into action. It generates a query embedding and performs a similarity search against the document embeddings stored within Elasticsearch. The similarity function meticulously calculates the semantic proximity between the query and document embeddings, identifying the most relevant documents based on their similarity scores. This approach ensures that Husky AI stays in sync with the evolving conversation context, retrieving the most pertinent information at each turn. The result is a system that generates responses that are not only accurate but also exhibit remarkable coherence and contextual relevance. 2.3. Ensemble of Specialized Language Models: A Symphony of Expertise Husky AI takes response generation to new heights by employing an ensemble of specialized language models, orchestrated by the MultiModelAgent class. Each model within the ensemble is meticulously trained for specific tasks or domains, contributing its unique expertise to the response generation process. When a user query is received, the MultiModelAgent leverages the retrieved documents and conversation context to generate responses from each language model in the ensemble. These individual responses are then carefully combined and processed to select the optimal response, taking into account factors such as relevance, coherence, and factual accuracy. By harnessing the strengths of specialized models like BlenderbotConversationalAgent, HFConversationalModel, and MyConversationalAgent, Husky AI can handle a wide range of topics and generate responses tailored to specific domains or tasks. 2.4. Integration of CustomWebRetriever: The Game Changer Husky AI takes adaptability and knowledge expansion to new heights with the integration of the CustomWebRetriever class. This powerful tool enables the system to dynamically retrieve and incorporate external data from the web, significantly expanding Husky AI's knowledge base and enhancing its contextual understanding by providing access to real-time information. Under the hood, the CustomWebRetriever class leverages the Serper API to conduct web searches and retrieve relevant documents based on user queries. It generates query embeddings using sentence transformers and utilizes these embeddings to ensure that the retrieved information aligns closely with the user's intent. The impact of the CustomWebRetriever on Husky AI's knowledge acquisition is profound. By incorporating this component into its pipeline, Husky AI gains access to a vast reservoir of external knowledge. It can retrieve up-to-date information from the web and dynamically adapt to new domains and topics. This dynamic knowledge evolution empowers Husky AI to handle a broader spectrum of information needs and provide accurate and relevant responses, even for niche or evolving topics. Iterative Learning: The Continuous Improvement Engine One of the key strengths of Husky AI lies in its ability to learn and improve over time through iterative learning. The system's knowledge base and response generation capabilities are continuously refined based on user interactions, ensuring a constantly evolving and adapting AI. 3.1. Learning from Interactions With every user interaction, Husky AI diligently analyzes the conversation history, user feedback (implicit or explicit), and the effectiveness of the chosen response. This analysis provides invaluable insights that help the system refine its understanding of user intent, identify areas for improvement, and strengthen its knowledge base. 3.2. Refining Response Generation The insights gleaned from user interactions are then used to refine the response generation process. Husky AI can dynamically adjust the weights assigned to different language models within the ensemble, prioritize specific information retrieval strategies, and optimize the response selection criteria based on user feedback. This continuous learning cycle ensures that Husky AI's responses become progressively more accurate, coherent, and user-centric over time. 3.3. Adaptability Across Applications The iterative learning mechanism in Husky AI fosters generalizability, enabling the system to adapt to diverse applications. As Husky AI encounters new domains, topics, and user interaction patterns, it can refine its knowledge and response generation strategies accordingly. This adaptability makes Husky AI a valuable tool for a wide range of use cases, from customer support and virtual assistants to content generation and knowledge management. Experimental Results and Analysis While traditional evaluation metrics provide valuable insights into the performance of generative AI systems, they may not fully capture the unique strengths and capabilities of Husky AI's AIL-powered architecture. The system's ability to dynamically acquire knowledge, continuously learn through user interactions, and leverage the synergy of its components presents challenges for conventional evaluation methods. 4.1. The Limitations of Traditional Metrics Traditional evaluation metrics, such as precision, recall, and F1 score, are designed to assess the performance of individual components or specific tasks. However, Husky AI's true potential lies in the seamless integration and collaboration of its various modules. Attempting to evaluate Husky AI using isolated metrics would be like judging a symphony by focusing on individual instruments rather than appreciating the harmonious performance of the entire orchestra. Moreover, traditional metrics may not adequately account for Husky AI's ability to continuously learn and update its knowledge base through the `CustomWebRetriever`. The system's dynamic knowledge acquisition capabilities enable it to adapt to new domains and provide accurate responses to previously unseen topics. This ongoing learning process, driven by user interactions, is a progressive feature that may not be fully reflected in conventional evaluation methods. 4.2. Showcasing Husky AI's Strengths through Real-World Scenarios To truly showcase Husky AI's superior capabilities, it is essential to evaluate the system in real-world scenarios that highlight its adaptability, contextual relevance, and continuous learning. By engaging Husky AI in diverse conversational contexts and assessing its performance over time, we can gain a more comprehensive understanding of its strengths and potential. 4.2.1. Dynamic Knowledge Acquisition and Adaptation To demonstrate Husky AI's dynamic knowledge acquisition capabilities, the system can be exposed to new domains and topics in real-time. By observing how quickly and effectively Husky AI retrieves and incorporates relevant information from the web, we can assess its ability to adapt to evolving knowledge landscapes. This showcases the power of the `CustomWebRetriever` in expanding Husky AI's knowledge base and enhancing its contextual understanding. 4.2.2. Continuous Learning through User Interactions Husky AI's continuous learning capabilities can be evaluated by engaging the system in extended conversational sessions with users. By analyzing how Husky AI refines its responses, improves its understanding of user intent, and adapts to individual preferences over time, we can demonstrate the effectiveness of its iterative learning mechanism. This highlights the system's ability to learn from user feedback and deliver increasingly personalized and relevant responses. 4.2.3. Contextual Relevance and Coherence To assess Husky AI's contextual relevance and coherence, the system can be evaluated in real-world conversational scenarios that require a deep understanding of context and the ability to maintain a coherent dialogue. By engaging Husky AI in multi-turn conversations spanning various topics and domains, we can demonstrate its ability to generate accurate, contextually relevant, and coherent responses. This showcases the power of the ensemble model and the synergy between the system's components. Husky AI sets a new standard for intelligent, adaptable, and user-centric systems. Its AIL-powered architecture paves the way for the development of AI systems that can seamlessly integrate with the dynamic nature of real-world knowledge and meet the diverse needs of users. With its continuous learning capabilities and real-time knowledge acquisition, Husky AI represents a significant step forward in the quest for truly intelligent and responsive AI systems. Samples of outputs and debug logs showcasing its abilities. I would be happy to show more examples. https://preview.redd.it/hpfqkg6arazc1.png?width=1920&format=png&auto=webp&s=c332d26dc0144842ff30c1ba0a1c1d435f14e6b3 https://preview.redd.it/lgq7agebrazc1.png?width=1904&format=png&auto=webp&s=8cc15dd15fe3e480161819dd9614b15ad114ad37 https://preview.redd.it/476a0n20vazc1.png?width=2548&format=png&auto=webp&s=837870eff7b51eef932f46498a662b1846f0591e submitted by /u/siphonfilter79 [link] [comments]

• The AI Risk Matrix: A Strategy for Risk Mitigation
  by /u/superc0w (Artificial Intelligence) on May 9, 2024 at 12:05 am

  submitted by /u/superc0w [link] [comments]

• Are you comfortable telling your boss that you use AI in the workplace? 52% say no
  by /u/Similar_Diver9558 (Artificial Intelligence Gateway) on May 8, 2024 at 11:01 pm

  https://www.forbes.com.au/news/leadership/workers-dont-want-bosses-knowing-they-use-ai/ View Poll submitted by /u/Similar_Diver9558 [link] [comments]

• Looking to build a chat bot - where should I go?
  by /u/Modern_chemistry (Artificial Intelligence Gateway) on May 8, 2024 at 10:37 pm

  So I’m a teacher and I was able to use playlab.io and build some pretty awesome things, but im interested in building personal bots in the same manner. For example: some sort of daily journal, health monitor, life coach, etc etc to help me with everyday things like career advice or random ideas. a philosopher steeped in XYZ and I want help philosophizing over some random thought I had which my girlfriend has already heard enough of. a school teacher helping to lesson plan and brainstorm ideas and connecting different concepts. a personal teaching assistant to help keep me on track and knows my scope and sequence AND a personal assistant to help me with my scheduling and what not. Where can I build these that’s safe, reliable, and free? Can I do this all on chatGPT+? My only experience building bots is with playlab.ai. submitted by /u/Modern_chemistry [link] [comments]

• Best way to get better at AI
  by /u/Personal_Concept8169 (Artificial Intelligence Gateway) on May 8, 2024 at 10:34 pm

  Hello everyone! Hope yall having a good day. I'll just jump straight into it. I'm a computer science student (second year), I do have experience with python. I do understand linear algebra, statistics, and calculus, I do have experience coding AI, i've built a NN from scratch, trying to learn pytorch now... I completed the deep learning specialization on coursera and have dabbled with the stanford AI courses. Still despite this I feel like I know nothing. I mean I can barely complete basic kaggle problems, I've done two so far, titanic and MNIST. MNIST i coded without anything but numpy, and that took me 3 weeks of debugging and all that. With titanic, I decided to try to learn pytorch but it shit on me and It's been a month and I'm just going to start another problem from scratch again I think... I'm incredibly slow with these problems, data wrangling is fine for me, i don't really know what my issue is everything just breaks all the time. I know it's probably normal, but is there any other materials I should be picking up? Or should I just keep pushing through these problems? I'm completely self taught by the way. (no ai courses in my uni) And this is just with basic networks, I mean i haven't even started on GANS and convolutional networks and recursive and yadda yadda. It's a weird state where I'm not a beginner but I'm not an intermediate and just tryna get yall's input on the best way forward. tysm in advance for any/all advice. submitted by /u/Personal_Concept8169 [link] [comments]

• Google DeepMind’s new AI can model DNA, RNA, and ‘all life’s molecules’
  by /u/Rare_Adhesiveness518 (Artificial Intelligence Gateway) on May 8, 2024 at 10:04 pm

  Google DeepMind is introducing an improved version of its AI model that predicts not just the structure of proteins but also the structure of “all life’s molecules.” The work from the new model, AlphaFold 3, will help researchers in medicine, agriculture, materials science, and drug development test potential discoveries. Want to stay ahead of the curve in AI and tech? take a look here. Key points: AlphaFold 3, can predict the structure of all life's molecules, not just proteins, including DNA, RNA and smaller molecules. This is a significant improvement from previous versions. AlphaFold 3 uses a similar method to AI image generators to predict how different molecules fit together. This method is called diffusion. DeepMind is making AlphaFold 3 and the AlphaFold Server available to some researchers for free, with a focus on non-commercial uses. They are also working on responsible deployment of the model considering biosecurity risks. Source (The Verge) PS: If you enjoyed this post, you’ll love my ML-powered newsletter that summarizes the best AI/tech news from 50+ media sources. It’s already being read by hundreds of professionals from OpenAI, HuggingFace, Apple… submitted by /u/Rare_Adhesiveness518 [link] [comments]

• Fine-tuning
  by /u/pelatho (Artificial Intelligence Gateway) on May 8, 2024 at 8:55 pm

  I've been developing a AI Companion app for few months. It's coming along nicely, but the complexity of my prompts have reached a point where some models struggle to understand and sometimes get lost and start producing output that I don't like. I've experimented with different models and while the majority of models fail to comprehend the prompts (They are fairly long and include personality traits, recent events, active memory entries, and instructions for writing messages and lists of available commands etc.). Some models, in particular Cohere's Command R Plus is astonishingly good - however, I may not be able to use this model since my project is NSFW in nature. The only alternative I've found that is somewhat usable is Mistrals "Mistral Large" model - however, it often looses track of context and ends up asking the same question over and over. So, my question is, could I take a slightly smaller model, like a 70B model and fine-tune it? Fine-tuning and hosting of models seems to be fairly straight-forward and easy enough for me to accomplish via together.ai. But, how much training data do I really need? 30k lines? 200k? 1 million? I have no idea. I imagine my dataset needs to contain snippets of certain likely phrases or instructions in the system prompt, paired with a user message and assistant response. For example ("pseudocode"): system prompt: Commands: web_browse (browse the web, arguments: query) user: {"message": "What's the latest news in AI?", "time": "just now"} assistant: {"message": "Let me see...", "command": {"name": "web_browse", "arguments": {"query": "Artificial Intelligence news"}}} If anyone has experience in this area, I'd be happy to learn! Thanks in advance. submitted by /u/pelatho [link] [comments]

• OpenAI Is ‘Exploring’ How to Responsibly Generate AI Porn
  by /u/wiredmagazine (Artificial Intelligence) on May 8, 2024 at 8:07 pm

  submitted by /u/wiredmagazine [link] [comments]

• Any Mimico AI user here?
  by /u/chevelle_dude (Artificial Intelligence Gateway) on May 8, 2024 at 8:04 pm

  Hi all, I've been using Mimico for a few months now on my Android phone. Paid for a lifetime subscription. Today I can no longer open my app. An error shows stating "The app installed on your device is not recognized and could harm your device. Search for it on Google Play to reinstall it." However when I search Google Play, the app is no longer available. I would contact their support, but only way I know is through the app itself. submitted by /u/chevelle_dude [link] [comments]

• A Daily chronicle of AI Innovations May 08 2024: 👨‍⚕️Google built medical AI that can train itself and outperform real doctors 🕵️‍♂️Microsoft launches AI chatbot for spies 🖼️OpenAI’s new tool detects 98% DALL-E 3 generated images 📣Meta expands AI-powered creativity tools for ads + 🎨AI Jobs
  by /u/enoumen (Artificial Intelligence Gateway) on May 8, 2024 at 7:38 pm

  submitted by /u/enoumen [link] [comments]