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Depends on the definition of reasoning: 1) think, understand, and form judgments by a process of logic. —- LLMs do not think, nor do they understand; they als
by garciasn 11mo ago
Depends on the definition of reasoning:
1) think, understand, and form judgments by a process of logic.
—- LLMs do not think, nor do they understand; they also cannot form ‘judgments’ in any human-relatable way. They’re just providing results in the most statistically relevant way their training data permits.
2) find an answer to a problem by considering various possible solutions
—- LLMs can provide a result that may be an answer after providing various results that must be verified as accurate by a human, but they don’t do this in any human-relatable way either.
—-
So; while LLMs continue to be amazing mimics, thus they APPEAR to be great at ‘reasoning’, they aren’t doing anything of the sort, today.
- CamperBob2 11mo agoExposure to our language is sufficient to teach the model how to form human-relatable judgements. The ability to execute tool calls and evaluate the results takes care of the rest. It's reasoning.
- garciasn 11mo agoSELECT next_word, likelihood_stat FROM context ORDER BY 2 DESC LIMIT 1 is not reasoning; it just appears that way due to Clarke’s third law.
- CamperBob2 11mo ago(Shrug) You've already had to move your goalposts to the far corner of the parking garage down the street from the stadium. Argument from ignorance won't help.
- int_19h 11mo agoSure, at the end of the day it selects the most probable token - but it has to compute the token probabilities first, and that's the part where it's hard to see how it could possibly produce a meaningful log like this without some form of reasoning (and a world model to base that reasoning on). So, no, this doesn't actually answer the question in a meaningful way.
- deleted 11mo ago[deleted]