The article body does not presume they reason.
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)
To advance further it would need the ability to abstract away the general situation shape and pattern recognize similar situations.
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.
JackSlateur•1h ago
throw310822•1h ago
3848499449•34m ago
ToValueFunfetti•26m ago
chrisjj•34m ago
throw310822•10m ago
azakai•54m ago
We see some signs of reasoning, but also we understand little about how they work.
michaelchisari•40m ago
blooalien•35m ago
This is the part that so many folks just don't seem to understand (probably because it's been labeled as "thinking" or "reasoning" mode, and people assume that words have meaning). It's not reasoning or thought. It's spewing tokens pretending to "think", but it's actually just generating extra "context" to help the final answer be more coherent. The model isn't doing anything it doesn't already do. It's just doing more of it to improve the quality of the final answer displayed to the user.
dataflow•7m ago
Leonard_of_Q•6m ago
Do LLMs 'think'? I 'think' they do in a way. I don't really know how I think myself but I know I do and therefore I am (thanks, Descartes). I have a somewhat better grasp of the way LLMs 'think'. They do so sequentially, building a chain of descriptors which best fit the problem and the preceding descriptors. I suspect I do something not entirely dissimilar- i.e. I imagine 'worlds' which are like the current one changed in some way so they the problem I'm working on is reduced, then refine those until it is resolved - but in a massively parallel way.
arcanemachiner•44m ago
otabdeveloper4•27m ago
Do they actually help? Are you sure?