MIT CSAIL: GPT-6 Astra edits Qwen's parameters
Researchers at MIT CSAIL have published initial results on their project "Weight-Space Programming," which uses LLMs to read and write the parameters of other neural networks. They report that GPT-6 Astra directly edited 0.016% of the parameters of Qwen3.5-0.8B, reducing thought loops where it repeats thoughts without reaching an answer. This improvement was seen with up to 50 forward passes for…
Key points
- MIT CSAIL researchers tested GPT-6 Astra on Qwen3.5-0.8B
- GPT-6 Astra edited 0.016% of Qwen's parameters
- Improvement seen with up to 50 forward passes
Model page: GPT-6 Astra →
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AI Morning Paper | November 4: GPT-6 Astra directly edits parameters of other AIs, Claude supports automatic connection to services
note.com · 3 November 2026
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