[#Article] @xai announces the upcoming availability of Grok 1.5 Vision https://actuia.com/actualite/xai-annonce-la-prochaine-disponibilite-de-grok-15-vision/ … #AI #artificialintelligence
LLMS
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WhatsApp gets AI upgrade powered by Meta’s Llama
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4/ WhatsApp is getting an AI upgrade They're testing new generative AI features powered by Meta's Llama. Get ready for even smarter and more creative conversations with your friends.
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Elon Musk’s Grok-1.5: a new multimodal AI
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1/ Elon Musk just dropped a bombshell His AI company revealed "Grok-1.5", an AI that can understand images as well as text. Think GPT-4V and Gemini Pro 1.5, but with eyes This could be a game-changer.
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Livestream: Reka Core/Flash/Edge Paper Review
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[Livestream] Reading Reka Core/Flash/Edge Paper https://t.co/LivgUfS3au
— swyx 🐣 (@swyx) 16 avril 2024[Livestream] Reading Reka Core/Flash/Edge Paper
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Understanding How Large Language Models Actually Work
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It's not an unreasonable mental model to form to be honest – enormous weird blobs of vector floating point matrices and token embeddings are hardly an obvious way that this technology might work
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Fine-tuning vs RAG: Teaching AI Models Effectively
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This could also explain why so many people instantly assume that "fine-tuning" a model is the obvious right way to teach it new information, as opposed to using more effective but less obvious techniques like RAG (not helped by that being a pretty terrible acronym)
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Lack of transparency in AI model training data usage
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Right, the most frustrating thing about this is that the complete lack of of transparency about how training works (and how the data is used) means it's impossible to confidently state how it all really works
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Common Misconceptions About How AI Models Learn
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I wonder how common it is for people to confidently hold an inaccurate idea of how AI models work where they believe that anything they show the model is instantly memorized and added to its "knowledge" of the world
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How Models Actually Work: Training Misconceptions
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I'm beginning to suspect that many people – including many corporate decision makers – have a confident but inaccurate model of how models work, where they think that absolutely anything the model sees is "training" which it then perfectly memorizes and adds to its knowledge
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LLMs Unnecessary When Cheaper Models Perform Better
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You absolutely don't need LLMs for this. Using LLMs here where a model that's 0.1% as expensive would work 5x better would be a show of gross incompetence.