Some people claim Astra is significantly better than anything else
and significantly more token-efficient, and others (like you) say it's meh and way more expensive to boot. I really don't know what to think.
Kind of a tangent, but one thing I am curious about is to what degree the Navier-Stokes result announced today was primarily a brute-forced result based on the 'program' previously established by researchers to find counterexamples (blowups), or whether the model actually added significant/novel intellectual value beyond its ability to run at arbitrary parallelism. With 10K agents and a staggering $15M in compute (IIRC), I am feeling like a lot of the former may have been involved, but I don't really understand either the problem or the approach (or, indeed, the solution).
Obviously the potential for parallelism and coordination between so many agents is quite scary by itself, but I think brute force by 10K mediocre AI mathematicians is much less scary than ~one AI mathematician reasoning its way through the problem where all human attempts have failed. It seems fairly obvious that massive parallelism lends itself to brute-force counterexample-finding, and I suspect it isn't a coincidence that most of the touted AI math results have been counterexamples.
It's all still quite scary, but coming full circle: I really don't know what to think.