Can We Understand How Large Language Models Reason?
25 points by adunk 2 hours ago | 19 comments

gfody 49 seconds ago
there's a 2MP about the related paper: https://www.youtube.com/watch?v=l72ufA-4SzE
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warumdarum 12 minutes ago
They dont. They have input that runs through a invisible stochastic canyon. As long as there is previous experience the stochastic canyon never ends. If there is none or isignificant one, or it runs out of tokkens, it hallucinates and the illusion falls apart. There is no reasoning, just the invisible grand canyon of all of human experience and knowledge. PS: try to get it to retell you a clichee movie or book and you can see life near the end, how the delta of all the same movies opens up into wildly different endings.

To advance further it would need the ability to abstract away the general situation shape and pattern recognize similar situations.

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CrzyLngPwd 14 minutes ago
My toaster doesn't reason, and neither do the current clankers.
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calf 12 minutes ago
One plausible reason I thought of that we may not understand neural nets is that by their nature their power grows with ever-more complex connections and weights.

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)

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otabdeveloper4 14 minutes ago
They don't reason.
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analog31 51 minutes ago
Do LLMs have Qualia?
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chrisjj 21 minutes ago
Clickbait article title.

The article body does not presume they reason.

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JackSlateur 57 minutes ago
Do they ?
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azakai 41 minutes ago
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.

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michaelchisari 27 minutes ago
Do we see actual signs of reasoning or is it anthropomorphism? We have an innate tendency to do so as humans.
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blooalien 21 minutes ago
> Do we see signs of reasoning or is it anthropomorphism?

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.

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azakai 20 minutes ago
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.

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michaelchisari 11 minutes ago
The papers linked in the article discuss the mechanical operations that simulate reasoning. Intelligence is data efficiency and I don't see a strong argument that reasoning can exist if it requires a world's worth of data.

That doesn't mean that simulated reasoning isn't useful, it's wildly useful. But a thing is not its simulation.

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arcanemachiner 31 minutes ago
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.
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otabdeveloper4 13 minutes ago
> that help to improve the final output

Do they actually help? Are you sure?

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throw310822 47 minutes ago
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.
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chrisjj 20 minutes ago
The Eliza effect strikes.
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3848499449 20 minutes ago
they don't tho
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ToValueFunfetti 13 minutes ago
For the love of all that is sacred, please stop doing this. I'm begging you. The whole social media landscape is dying and you are creating a throwaway to participate in ruining this small corner. I assume this is not your first. And no one is convinced by this! The guidelines are there for your benefit as well. You achieve nothing but hastening the destruction of one of the last half-decent communities. Sorry for the melodrama.
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