Comment by dingnuts

5 days ago

> Latent reasoning doesn't really appear until around 100B params.

Please provide a citation for wild claims like this. Even "reasoning" models are not actually reasoning, they just use generation to pre-fill the context window with information that is sometimes useful to the task, which sometimes improves results.

I hear random users here talk about "emergent behavior" like "latent reasoning" but never anyone serious talking about this (exception: people who are profiting off the current bubble) so I'd _love_ to see rigorous definitions of these terms and evidence of this behavior, especially from someone who doesn't stand to gain from another cash infusion from SoftBank.

I suspect these things don't exist. At the very most, they're a mirage, and exist in the way a rainbow does. Go on and try to find that pot of gold, eh?

> Please provide a citation for wild claims like this. Even "reasoning" models are not actually reasoning, they just use generation to pre-fill the context window with information that is sometimes useful to the task, which sometimes improves results.

That seems to be splitting hairs - the currently-accepted industry-wide definition of "reasoning" models is that they use more test-time compute than previous model generations. Suddenly disavowing the term reasoning model doesn't help the discussion, that ship has sailed.

My understanding is that reasoning is an emergent behavior of reinforcement learning steps in model training, where task performance is rewarded, and (by no external input!) the model output starts to include phrases ala "Wait, let me think". Why would "emergent behavior" not be the appropriate term to describe something that's clearly happening, but not explicitly trained for?

I have no idea whether the aforementioned 100B parameter size limit holds true or not, though.

  • Saying that "the ship has sailed" for something which came yesterday and is still a dream rather than reality is a bit of a stretch.

    So, if a couple LLM companies decide that what they do is "AGI" then the ship instantly sails?

  • > currently-accepted industry-wide definition of "reasoning"

    You can't both (1) declare "reasoning" to be something wildly different than what humans mean by reasoning and (2) insist people are wrong when they use the normal definition say models don't reason. You gotta pick a lane.

    • I don't think its too problematic, its hard to say something is "reasoning" without saying what that something is, for another example of terms that adjust their meaning to context for example, the word "cache" in "processor cache", we know what that is because its in the context of a processor, then there's "cache me outside", which comes from some tv episode.

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    • Or you could accept that sometimes fields contain terms-of-art that are non-intuitive to outsiders. Go ask an astromer what their working definition of a metal is.

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> Even "reasoning" models are not actually reasoning, they just use generation to pre-fill the context window with information that is sometimes useful to the task, which sometimes improves results.

I agree that seems weak. What would “actual reasoning” look like for you, out of curiosity?

  • Not parent poster, but I'd approach it as:

    1. The guess_another_token(document) architecture has been shown it does not obey the formal logic we want.

    2. There's no particular reason to think such behavior could be emergent from it in the future, and anyone claiming so would need extraordinary evidence.

    3. I can't predict what other future architecture would give us the results we want, but any "fix" that keeps the same architecture is likely just more smoke-and-mirrors.

    • Seems to fall apart at 1

      >1. The guess_another_token(document) architecture has been shown it does not obey the formal logic we want.

      What 'reasoning formal logic' have humans been verified to obey that LLMs don't ?

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  • It's the same bitching every time an LLM post can be responded to. ITS NOT THINKING!!! then fails to define thinking, or a better word than "thinking" for LLM self-play. I consider these posts to be on par for quality with "FRIST!!!!!!" posts.

    • Idk I think saying it’s “computing” is more precise because “thinking” applies to meatbags. It’s emulating thinking.

      Really I just think that anthropomorphizing LLMs is a dangerous road in many ways and really it’s mostly marketing BS anyway.

      I haven’t seen anything that shows evidence of LLMs being anything beyond a very sophisticated computer system.

    • Do submarines swim? Thinking is something that doesn’t happen inside a machine. Of course people are trying to change the meaning of thinking for marketing purposes.

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