"Also notable: 4.7 now defaults to NOT including a human-readable reasoning token summary in the output, you have to add "display": "summarized" to get that"

I did not follow all of this, but wasn't there something about, that those reasoning tokens did not represent internal reasoning, but rather a rough approximation that can be rather misleading, what the model actual does?

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motoboi 7 hours ago | parent | next [-]

The reasoning is the secret sauce. They don't output that. But to let you have some feedback about what is going on, they pass this reasoning through another model that generates a human friendly summary (that actively destroys the signal, which could be copied by competition).

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XenophileJKO 6 hours ago | parent [-]

Don't or can't.

My assumption is the model no longer actually thinks in tokens, but in internal tensors. This is advantageous because it doesn't have to collapse the decision and can simultaneously propogate many concepts per context position.

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ainch 6 hours ago | parent | next [-]

I would expect to see a significant wall clock improvement if that was the case - Meta's Coconut paper was ~3x faster than tokenspace chain-of-thought because latents contain a lot more information than individual tokens.

Separately, I think Anthropic are probably the least likely of the big 3 to release a model that uses latent-space reasoning, because it's a clear step down in the ability to audit CoT. There has even been some discussion that they accidentally "exposed" the Mythos CoT to RL [0] - I don't see how you would apply a reward function to latent space reasoning tokens.

[0]: https://www.lesswrong.com/posts/K8FxfK9GmJfiAhgcT/anthropic-...

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haellsigh 6 hours ago | parent | prev | next [-]

If that's true, then we're following the timeline of https://ai-2027.com/

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magicalist 3 hours ago | parent | next [-]

> If that's true, then we're following the timeline

Literally just a citation of Meta's Coconut paper[1].

Notice the 2027 folk's contribution to the prediction is that this will have been implemented by "thousands of Agent-2 automated researchers...making major algorithmic advances".

So, considering that the discussion of latent space reasoning dates back to 2022[2] through CoT unfaithfulness, looped transformers, using diffusion for refining latent space thoughts, etc, etc, all published before ai 2027, it seems like to be "following the timeline of ai-2027" we'd actually need to verify that not only was this happening, but that it was implemented by major algorithmic advances made by thousands of automated researchers, otherwise they don't seem to have made a contribution here.

[1] https://ai-2027.com/#:~:text=Figure%20from%20Hao%20et%20al.%...

[2] https://arxiv.org/html/2412.06769v3#S2

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butlike 3 hours ago | parent | prev | next [-]

Hilariously, I clicked back a bunch and got a client side error. We have a long way to go. I wouldn't worry about it.

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matltc 6 hours ago | parent | prev | next [-]

Care to expound on that? Maybe a reference to the relevant section?

	▲	ACCount37 6 hours ago \| parent \| next [-]
		Ctrl-F "neuralese" on that page.
	▲	9991 6 hours ago \| parent \| prev [-]
		You should just read the thing, whether or not you believe it, to have an informed opinion on the ongoing debate.

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9991 6 hours ago | parent | prev | next [-]

That's not supposed to happen til 2027. Ruh roh.

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literalAardvark 5 hours ago | parent | prev [-]

Only if you ignore context and just ctrl-f in the timeline.

What are you, Haiku?

But yeah, in many ways we're at least a year ahead on that timeline.

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JoshuaDavid 4 hours ago | parent | prev | next [-]

Don't.

The first 500 or so tokens are raw thinking output, then the summarizer kicks in for longer thinking traces. Sometimes longer thinking traces leak through, or the summarizer model (i.e. Claude Haiku) refuses to summarize them and includes a direct quote of the passage which it won't summarize. Summarizer prompt can be viewed [here](https://xcancel.com/lilyofashwood/status/2027812323910353105...), among other places.

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WhitneyLand 6 hours ago | parent | prev | next [-]

No, there is research in that direction and it shows some promise but that’s not what’s happening here.

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XenophileJKO 5 hours ago | parent [-]

Are you sure? It would be great to get official/semi-official validation that thinking is or is not resolved to a token embedding value in the context.

	▲	astrange 4 hours ago \| parent [-]
		You can read the model cards. Claude thinks in regular text, but the summarizer is to hide its tool use and other things (web searches, coding).

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6 hours ago | parent | prev | next [-]

[deleted]

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alex7o 6 hours ago | parent | prev | next [-]

Most likely, would be cool yes see a open source Nivel use diffusion for thinking.

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motoboi 5 hours ago | parent | prev [-]

Don't. thinking right now is just text. Chain of though, but just regular tokens and text being output by the model.

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boomskats 7 hours ago | parent | prev | next [-]

'Hey Claude, these tokens are utter unrelated bollocks, but obviously we still want to charge the user for them regardless. Please construct a plausible explanation as to why we should still be able to do that.'

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dheera 6 hours ago | parent | prev [-]

Although it's more likely they are protecting secret sauce in this case, I'm wondering if there is an alternate explanation that LLMs reason better when NOT trying to reason with natural language output tokens but rather implement reasoning further upstream in the transformer.