Comment by usef-

Comment by usef- a day ago

This isn't about being AGI or not, and it's not "out of thin air".

Modern implementations of LLMs can "do research" by performing searches (whose results are fed into the context), or in many code editors/plugins, the editor will index the project codebase/docs and feed relevant parts into the context.

My guess is they either were using the LLM from a code editor, or one of the many LLMs that do web searches automatically (ie. all of the popular ones).

They are answering non-stackoverflow questions every day, already.

nobunaga 18 hours ago

Yeah, doing web searches could be called research but thats not what we are talking bout. Read the parent of the parent. Its about being able to answer questions thats not in its training data. People are talking about LLMs making scientific discoveries that humans haven't. A ridiculous take. Its not possible and with the current state of tech never will be. I know what LLMs are trained on. Thats not the topic of conversation.

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oezi 16 hours ago

A large part of research is just about creatively re-arranging symbolic information and LLMs are great at this kind of research. For example discovering relevant protein sequences.

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semiquaver 15 hours ago

> Its about being able to answer questions thats not in its training data.
This happens all the time via RAG. The model “knows” certain things via its weights, but it can also inject much more concrete post-training data into its context window via RAG (e.g. web searches for documentation), from which it can usefully answer questions about information that may be “not in its training data”.

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