MIT researchers have demonstrated how frontier AI models can directly interpret and modify neural network weights without conventional gradient-based training. In experiments, OpenAI’s GPT-6 Astra corrected reasoning loops in Qwen3.5-0.8B, increasing its MATH-500 score from 7.9% to 48.1% by modifying just 0.016% of its weights.
MIT Researchers Show How GPT-6 Astra Can Read and Edit Neural Network Weights Without Training