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amlutotoday at 3:08 PM1 replyview on HN

Can we take a step back here? Both OpenAI’s and Anthropic’s models think in encryptedese, and it seems thoroughly absurd to think that the entire world should trust those two companies to adequately monitor the plaintext or, for that matter, to have their monitoring systems aligned with what is actually good for the world.

If you want to monitor your model, you need to start with an inference provider that gives you the entire output and possibly even run it yourself to get access to the internal states. And if you think the KV cache and (when present) the recurrent state don’t encode a lot of “thought”, you are fooling yourself.

FWIW, I think most model architectures at least have the property that latent state can’t propagate from higher layers to lower layers by any route other than the output tokens. But even a two-iteration structure could be designed so that the last layer produces a vector that enters the first layer, once per token, and I bet it it would be very easy to train such a model to “think” in silence in the sense that the output tokens while thinking would all be one particular null token.


Replies

verdvermtoday at 4:17 PM

Internal vector recurrence is more or less what the Universal Transformer paper proposes. This recent paper does so by sharing the transformer weights in a single recurrence setup: https://arxiv.org/abs/2607.22083, and this one does so at a per-token level: https://arxiv.org/abs/2507.10524

I agree with you about not trusting Big Ai. I'm amazed that so much of HN is repeating the same darling -> demon with OpenAi/Anthropic that we did last decade with other SV darlings. Humans are forgetful beings