AI 导读
太不可思议了：MIT 研究人员称，GPT-6 Astra 仅直接编辑 Qwen 小模型 0.016% 的权重，就将其数学成绩从 7.9% 提升到 48.1%，全程无需基于梯度的训练。 这一结果指向能够直接诊断并改进其他模型的人工智能系统，是迈向自我改进 AI 的潜在一步。
正文
Absolutely incredible: MIT researchers say GPT-6 Astra improved a small Qwen model’s math score from 7.9% to 48.1% by directly editing just 0.016% of its weights, without gradient-based training.
The result points toward AI systems that can diagnose and improve other models directly, a potential step toward self-improving AI.
We asked GPT-6 Astra to edit Qwen3.5-0.8B weights to improve math. It directly changed only 0.016% of weights, fixing 0.8B's reasoning loops & improving math up to 6x and even instruction following 3x, without gradients or training. We call this Weight-Space Programming: frontier LLMs can now natively read/write neural network weights! 🧵 Blog: https://rikiyat.github.io/blog/weight-space-programming/在 X 查看被引用的帖子
来源：Chubby♨️ · x.com