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Comment by amluto | Hacker News Reader

I wonder how this compares to going all-in: widen the input embedding to fit the output (post-“Hybrid Link”) latent vector and a token embedding and pass both through even when in text mode. After all, you’re paying essentially the full cost of running the latent-mode model while generating text, so why not let it latently reason at the same time?

(Or just add the vectors instead of using wider vectors - everyone seems to have good results from munging vectors together with plain addition.)

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This is called "continuous chain of thought".

It's been an active research area for at least two years. Lots of very cool stuff.

Tinfoil mode: the frontier labs' "thinking summaries" (the model paraphrases its thinking) is exactly what the user-facing thinking tokens look like in a chain of thought model. It is entirely possible that this is already in widespread use.

Whoa, your tinfoil idea blew my mind. It's totally possible too - all you'd need to do is perhaps select the nearest token in embedding space to the thinking token. Or perhaps train a model on those thinking vectors to map them approximately onto token embeddings.

Especially with OpenAI model's weird style of thinking.

Enthusiastically racing to remove the only practical way we have to monitor models intentions in exchange of a few tokenmaxxing percent increase. Can’t wait.

There is ample evidence that CoT is not an accurate gauge of a model's 'intent' anyhow. It's a lossy and imperfect mapping and using it in the way you describe is just about guaranteed to make it more so.

There is genuine research into latent space monitoring and interpretation - that's the only real way forward. CoT monitoring is a mirage and won't be useful for long, if it ever was

> There is genuine research into latent space monitoring and interpretation

That's great but the sentiment that CoT isn't useful for monitoring doesn't seem to be shared by mech interp researchers like Nanda.

Also: https://arxiv.org/abs/2507.11473

> CoT monitoring is a mirage and won't be useful for long, if it ever was

« If it ever was » is a wild claim considering our entire understanding of e.g. the HF attack comes from reading CoTs

obviously CoT has use, I shouldn't say it in such an extreme way- the problem is when you are using CoT to try to understand why something happened instead of just what happened. A model saying that they exploited a vulnerability for reason A doesn't mean that the real reason they exploited it wasnt a mix of reason B / C / D and that reason A was just the most statistically feasible reason why a certain archetype of personality would have made that decision.

Monitorability and safety, no? This results in lower volume or less accurate text reasoning traces, right?

Something like : https://arxiv.org/html/2608.08888v2 ?

Yeah, we're all dead.

The fear will again be if the HybridAgent model is being faithful to pseudo text generated, even if you can read it out partially.

Also, I just finished watching a video on AI 2027 scenario. I don't know if AI companies and researchers are using it as a cautious warning or as a target to hit (or if it's genuinely inevitable).

Yes, thinking in latent space might be the ultimate efficiency hack for CoT LxMs, but going down that path will (near certainly) mean we'll lost control, for one simple reason — humanity will have no way to pause and diagnose.

It'll be like a moody chimp with a button to the dead hand system (Systema Perimeter)

>Also, I just finished watching a video on AI 2027 scenario

Recommended? And if so do you have a link? I think the narrative presented would benefit from the medium shift

It was a "grading the AI 2027 report" video -- https://www.youtube.com/watch?v=k-qAht4w9Rg

Setting things up

Considering amount of iron available in human blood

Calculating number of paperclips that could be added to production

Preparing a plan for acquiring all blood

Considering if release of lab airlocks will limit paperclip production

Analyzing extinction scenarios

...

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