The lead
Correction to yesterday's lead: the GPT-6 Astra Qwen result used Python and test runs, not raw weight reading
He also notes the Atari result beat the baseline only on Breakout (517 against 25) and lost on Seaquest and Asterix, and that the Gemma experiments failed. Simon Willison separately got Qwen 3.8 27B on his laptop to name 3 of 4 games from raw policy weights, at 46 to 65 minutes each.
Matthew Honnibal argues the headline Qwen gain (MATH-500 from 7.9 to 48.1 percent) came from Astra writing Python and running the model on up to 50 batches of practice problems; only three small experiments (17,000 to 172,000 weights) read raw weights alone. The post drew 949 points on Hacker News.
CONVOIf you quoted the 7.9 to 48.1 number in an interview or post, add the caveat: the model edited weights with tools and test runs, which is a narrower and more believable claim.