GoKawiilMIT researchers get GPT-6 Astra to read and edit other AI models' internals
MIT researchers showed that OpenAI's GPT-6 Astra model can interpret the internal numerical values of other neural networks well enough to predict what different components do, and can then edit those networks to improve performance, including on math tasks. The team, led by Rikiya Takehi, described the findings in a preprint posted on November 2.
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The work suggests frontier AI systems may be developing an emerging capacity to act on other models' internal workings, similar to a mechanic fixing an engine they didn't design, according to the researchers. Outside researcher Fazl Barez notes this could help automate existing AI-interpretability methods, though he cautions that the hoped-for safety benefits of such understanding remain largely untested.
- GPT-6 Astra can predict functions of components inside other AI models and edit them to improve capabilities like math.
- The research automates some existing 'interpretability' techniques used to study neural network internals.
- Experts caution the model doesn't truly understand the networks, and safety benefits of this approach are still unproven.
Source: nature.com — Gibney, 2026-11-13
Published there as: “This AI ‘mechanic’ can peer inside the black box of other neural networks”
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