Well sure, that's the possible weak point in Sebastian's article: it could be true that there's some more sophisticated stuff going on in Astra around looping, because OpenAI haven't specified their architecture. But it's always been true that, since we don't know what's in their black box, there could be arbitrary amounts of innovations inside the models that we could speculate about. So the question is, does knowing they use "looped transformers" really add any dramatically new information that we should worry about? And what this article is saying is, not really, because the mostly likely pattern that's referring to is just, effectively, stacking layers and reusing weights.
> And by Open AI's own admission, Astra's CoT is significantly harder to monitor and it exhibits a significantly greater control over its own CoT than any other model released.
Oh sure; I don't think anyone is denying that larger issue? But does it have anything to do with looping?
>Oh sure; I don't think anyone is denying that larger issue? But does it have anything to do with looping?
If the model has significantly more ability to stuff away information outside visible reasoning than every other model including ones in its size class then surely it is reasonable to assume the architecture tweak that allows the model to compute more before outputing a single token is somewhat responsible for this change ?