GoKawiil
Tech News
Analysts examining OpenAI's newly released GPT-6 Astra note it outperforms its GPT-5.6 predecessor across writing, math, coding, and especially 3D rendering tasks, jumping from 7.8% to 99.9% on the ARC-AGI-3 benchmark. Speculation has emerged that Astra uses a looped or recurrent-depth transformer architecture and may be concealing parts of its chain-of-thought reasoning process from users.
According to The Information, OpenAI's upcoming Astra model employs a technique called recurrent depth or opaque recurrence, letting it think outside the step-by-step chain-of-thought format used by most reasoning models. Reports indicate the technique's use in Astra is currently limited, but its introduction has drawn sharp criticism from AI safety researchers who worry about losing insight into model reasoning.
According to a report from The Information, OpenAI's forthcoming Astra model employs a technique called 'recurrent depth' or 'opaque recurrence,' which processes queries in loops rather than following the linear, step-by-step reasoning typical of current models. This approach reportedly makes it harder to trace how the model arrives at its answers through conventional chain-of-thought monitoring.