Transparency about the opaque serial depth is great, but this statement is consistent with Astra having a configurable "dial" that is currently set to a low depth but could be trivially increased. We need more info to see how concerning these architectural changes are, including: - Are there readily available ways to deploy this AI with much higher serial depth (that would be commensurately more performant)? This should include things like tiny amounts of fine-tuning to productively increase the number of iterations. - Is the AI a large or above-trend jump in opaque reasoning capabilities? (Capabilities within a single forward pass or ability to subvert a CoT monitor.) (If there are in fact any relevant changes—perhaps the reporting is inaccurate?) Additionally, I worry that this architectural change will naturally lead to much more depth in the future if this direction is pursued further. Specifically, I wonder: - Does the AI have an architectural change that makes it much more natural to massively scale up the depth in a future training run with a similar architecture? As in, does the architecture introduce some new depth/recurrent-iterations parameter that is very natural/performant to massively scale up relative to scaling up other things like width? The details of the answers to these questions matter. E.g., if there are only a few (recurrent) iterations and you could scale up the number of iterations, but this wouldn't be particularly performant/natural with this architecture, then this development would be a lot less concerning!