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Ted Chiang wrote a great piece about that: https://www.newyorker.com/tech/annals-of-technology/chatgpt-...

I think it's a solid description for a raw model, but it's less applicable once you start combining an LLM with better context and tools.

What's interesting to me isn't the stuff the LLM "knows" - it's how well an LLM system can serve me when combined with RAG and tools like web search and access to a compiler.

The most interesting developments right now are models like Gemma 3n which are designed to have as much capability as possible without needing a huge amount of "facts" baked into them.



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