HN commenters call the result shocking and significant
2 Nov 2 2:00 PM · 6d ago · 1 post · 7 comments · 2 sources · development 2 of 5
Early commenters describe being stunned that an LLM can edit another model's weights by hand to improve capability, comparing the implications to major past ML breakthroughs.
“This is insane... No human can go edit a brain to become better at math. This is just very, very surprising”
vessenesRikiya Takehi Researcher, author of the blog postGPT-6 Astra OpenAI LLM used as the weight-editing modelQwen3.5-0.8B Target model edited by Astra
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What people said 7 voices · verbatim
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> As a result, Astra spots and fixes a common failure of tiny reasoning models: they loop [13]. When the base model loops, it repeats the same text and rarely reaches an answer (85 of its first 96 practice answers ran to the 32,768-token limit). Astra traced the looping to one direction written by the MLPs of layers 15 and 19, and subtracted that…
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This is insane.Astra can, without tooling, determine what games small networks are trained on, can edit the weights of networks directly to improve outcomes, and can hand edit a small qwen model to improve its math skills by like 5x.I'm shook. If you'd asked me this morning whether LLMs have native understanding of their weights that is less than…
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My somewhat uninformed guess is that the weights of the target network (Qwen or Gemma), when they reach the context of the larger editor model (Astra), the attention process is doing some sort of PCA on the weights, conditional on the prompt ("make this better at games"), fetching the relevant weights from its own network (which serves as the…
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On balance I'm not that surprised that it can guess games by looking at the weights of a tiny neural net. A human can do the same by looking at the weights of an MLP trained on mnist, for example. With that simple structure, it's easy to look at the input layer and see that features correspond to the spatial location of objects of interest.I'm…
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I find this just completely shocking. I’m definitely skeptical. It just doesn’t line up with my understanding of how these models work. Is there really enough training data on direct weight editing to give a model this skill? Maybe it’s evidence that OpenAI has been creating a lot of training data on ML research. I’m surprised that was put into a…
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It's worth pointing out that this is a multi-trillion (probably) parameter model optimizing an 800 million parameter model. There is no indication that it can improve itself with this same methodology.
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I’m just a layman but this feels like a big discovery on par with attention is all you need. For an LLM to have such incredible intuition of weights feels very emergent and unanticipated?
All 5 developments of Researcher shows OpenAI's GPT-6 Astra hand-editing Qwen's… →
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