58 points allinonai 1 hour ago 24 comments

44za12 51 minutes ago | parent

Where are the benchmarks? Does it just speed up inference and reduce token usage or does it seem to improve accuracy on certain tasks as well?

notnullorvoid 43 minutes ago | parent

Did you even scan the paper? There are benchmarks right there starting on the 9th page.

D-Machine 15 minutes ago | parent

Even the abstract answers some of GPs questions. What is wrong with some of the posters here?

allinonai 32 minutes ago | parent

dang 27 minutes ago | parent

We'll put those links at the top as well. Thanks!

cwyers 32 minutes ago | parent

Oh cool, it's the Most Forbidden Technique

k__ 22 minutes ago | parent

Care to elaborate?

lnenad 19 minutes ago | parent

In short we no longer see text based reasoning traces meaning it's easier for the models to fool us in case of malicious plans.

kelseyfrog 19 minutes ago | parent

If you accept any of the AI-equivalents of Pascal's Wager, latent thinking represents an uninterpretable and thus unalignable portion of AI machinery. Ie: a malevolent AI can hide bad stuff from people and Manchurian candidate themselves after it's too late.

mycall 5 minutes ago | parent

That assumes nothing can detect or analyze it beforehand.

jlhawn 18 minutes ago | parent

the chain of thought is not auditable. The best you can do is have another model which later maps the intermediate latent states at every thinking iteration to text describing that latent state, but it's going to be lossy.

mycall 8 minutes ago | parent

Isn't this where everything is converging? Binary is more efficient than text for many system, including language.

andsoitis 2 minutes ago | parent

> Binary is more efficient than text for many system, including language.

It is not necessarily primarily about efficiency, but more the fact that a lot of thinking doesn't use language at all.

haolez 7 minutes ago | parent

But the chain of thought as text can be elusive, no? It might not be related with the actual "reasoning" of the model. There was a paper about this.

timschmidt 18 minutes ago | parent

He's referring to this technique's effect of obscuring interpretibility. Making it much more difficult to verify chains of thought and alignment.

modeless 17 minutes ago | parent

People at the big labs have been terrified of losing the chain of thought because they currently monitor it to prevent users from using their models in certain ways they consider unsafe or bad for their business. Personally I think chain of thought monitoring is a bad way to do this and obviously needs to be replaced by some way of analyzing the model's activations directly.

Lerc 11 minutes ago | parent

Agreed, having text as a reasoning layer impedes performance while giving a false sense of security.

It could be encoding anything in its adjective choices etc. The same thing that model providers are using for watermarking can used by the model itself for private thought.

Fe2O3 29 minutes ago | parent

This seems really cool, and it actually increases intelligence than just speeding up inference. How does it convert latent reasoning into human readable text?

jedbrooke 21 minutes ago | parent

maybe the font experts can check, but I’m pretty sure they’re using comic sans for the text in the diagrams :)

mobelkh 19 minutes ago | parent

comic sans is said to be pretty accessible for people with dyslexia

sheepscreek 7 minutes ago | parent

This is the way.

But now we also need new tools and techniques to audit intent. The last thing we want is models turning on us ‘for our own good’.

drivebyhooting 6 minutes ago | parent

In terms of safety and alignment, how is this different from looping or increasing the depth?