Neuroscientist uses GPT-6 Astra to derive a high-dimensional brain computation solution
A theoretical science researcher says Astra ran independently for 100 minutes with Max thinking to produce an initial derivation that matched large-network simulations, and he is excited about AI-assisted understanding of brain computation.
'I had assumed that this problem was analytically intractable. After working independently for 100 minutes with Max thinking, GPT-6 Astra produced the initial derivation, yielding a self-consistent problem whose solution matched simulations of large networks. I found this derivation intriguing, albeit complicated and somewhat mysterious (see Al Methodology in the paper). After investigating the structure of the proposed solution more deeply, together with Al models, I arrived at a physically transparent derivation.' 'Many people in the theoretical sciences are anxious about Al. However, in my field at least, we are nowhere close to fully understanding the high-dimensional computations unfolding in our brains. With Al, we could reach a level of understanding that so far we have only gestured toward. So, I am excited.'
Done in collaboration with GPT-6 Astra and Claude Opus 5.5.
This post quotes another post: x.com/d_g_clark/status/2108574780957905073
