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Earlier quoted context omitted.
Do they ?
Of course they do, how else do you think they manage to implement new features in large codebases, or to prove new theorems? But you don't even have to assume they do because of the results- you can read their chain of thought.
Earlier quoted context omitted.
The article answers this question, at least to the extent it can be answered, at this time. We see some signs of reasoning, but also we understand little about how they work.
Do we see actual signs of reasoning or is it anthropomorphism? We have an innate tendency to do so as humans.
Yes, we have a tendency to anthropomorphize, but (most) researchers are aware of this.
[stub for offtopicness] [[All: please don't post shallow-generic reactions to baity titles. Those are basically the same thing, a la https://en.wikipedia.org/wiki/Rubin_vase , and we're trying for something more substantive here.]]
[stub for offtopicness] [[All: please don't post shallow-generic reactions to baity titles. Those are basically the same thing, a la https://en.wikipedia.org/wiki/Rubin_vase , and we're trying for something more substantive here.]]
Earlier quoted context omitted.
Do they ?
Yes, there is an LLM feature that we have anthropomorphized as "reasoning" or "thinking", where an LLM has a scratch space where it can dump tokens that help to improve the final output.
Do they actually help? Are you sure?
Earlier quoted context omitted.
Of course they do, how else do you think they manage to implement new features in large codebases, or to prove new theorems? But you don't even have to assume they do because of the results- you can read their chain of thought.
[flagged]
So it is like the opposite of logical systems, in that the very design of neural net architecture is a mess of parameter "spaghetti code" which renders the entire thing a metaphorical encrypted black box. The more powerful an AI/AGI the more this would be the case, and this is analogous a complexity curve.
And so any effort to make sense of such black box computation would be like trying to reverse entropy, analogous to trying to recover information lost in waste heat. And that could be one fundamental barrier to understanding both human and artificial brains alike, relative to their internal complexity.
(Just thinking aloud my handwavy pet theory recently, I am not an expert and could be totally mistaken on this)
[stub for offtopicness] [[All: please don't post shallow-generic reactions to baity titles. Those are basically the same thing, a la https://en.wikipedia.org/wiki/Rubin_vase , and we're trying for something more substantive here.]]
To advance further it would need the ability to abstract away the general situation shape and pattern recognize similar situations.
Earlier quoted context omitted.
Do we see actual signs of reasoning or is it anthropomorphism? We have an innate tendency to do so as humans.
Yes, we do see signs of actual reasoning, see the papers linked in the article. (There are many others too.) Yes, we have a tendency to anthropomorphize, but (most) researchers are aware of this.
That doesn't mean that simulated reasoning isn't useful, it's wildly useful. But a thing is not its simulation.