Peeling the layers of #AI: From broad AI concepts to the niche realm of #GenerativeAI, each layer builds upon the next. Stay updated with @ingliguori for insights into AI's complex structure and master its potential with 'The Digital Edge' https://
bit.ly/3u4pILl #DeepLearning
GENERATIVE AI
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Understanding AI Layers: From Broad Concepts to Generative AI
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Novel One-Sentence Startup Pitch Structure Across AI Models
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Here's an interesting question to use to compare models: "GPT-4, Llama 3, Claude 3, Gemini 1.5, give me a novel structure for a one-sentence startup pitch and teach me how to use it"
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Document Chunking Techniques for Better RAG Applications
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But, How is Chunking Done? To create Better RAG applications, you need to know how to split or chunk the documents so you preserve the content while asking questions. Data Science Basics shows how to do this with LangChain https://
youtube.com/watch?v=tMwdl9
hFPns
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Llama 3: Dense Model Efficiency vs Sparse MoE Scaling Strategy
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Thing that most impresses me about Llama 3: how did they pack so much knowledge and reasoning into a dense 8b and a 70b so well, when everyone else has been scaling sparse MoEs. This still doesn’t mean having a lot of GPUs is not important. Probably even more important
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8B Model Enables Creation of Diverse AI Experiences
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8b is so good. Can create a lot more experiences with it. We have some ideas. Stay tuned!
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Can AI Achieve Superhuman Intelligence Beyond Training Data?
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I one discussion you see often is whether superhuman intelligence is possible, given that AI is human trained I don’t buy all of these points, but I think this is a well-laid out list of arguments AI may be able to be more “intelligent” than the source material it was trained on
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Over 1M AI Models Released Daily on Hugging Face
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Great article by @TechCrunch but what we've been saying for years is even more extreme than that. There's over 1M models on HF & thousands are released every day! Ultimately, there will be as many models as code repositories for every single company, use-case and features. The
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Open Models and Efficient Hardware Making AI More Accessible
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"The combination of powerful open models like LLaMA and highly efficient “AI-first” inference hardware like Groq’s could make advanced language AI more cost-effective and accessible to a wider range of businesses and developers." – @MichaelFNunez
