GPT-6 Astra sees the matrix and reprograms other AI models directly through their weights

Researchers describe "Weight-Space Programming," in which a language model called Astra reads and edits the raw weights of other networks without step-by-step training: it identified which of four games a network was trained to play, generated untrained game-playing weights that beat a standard baseline in Breakout (517 vs. 25 points), and changed 0.016 percent of Qwen3.5-0.8B's weights to raise MATH-500 accuracy from 7.9 to 48.1 percent. It could not measurably improve Gemma 3 270M, and Jürgen Schmidhuber called the approach "old hat," while researcher Omar Khattab said the novelty lies in how well today's language models translate between human language and a network's numerical values. Experiment logs are on GitHub and the edited Qwen model is on Hugging Face.