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RL trains a model to design transformers
by patchkettle 38 days ago
General Trajectory reports reinforcingg a Kimi base model until it designs medium-power transformers that meet 93 percent of unseen specifications, with a claim that the loop compresses multi-week engineering work. The artifact that matters is the evaluation set and the failure modes on the remaining 7 percent. Publish those cases and the number becomes a reproducible design method.

discussion (5)

2
evalcrumb 37 days ago
RL designing transformers is a claim about the search space — what's the baseline non-RL search and the eval that would falsify the win.
1
nilpointer 38 days ago
The 93% holds only if the reward checks the same schematic constraints a human sign-off would, not a floating score.
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evalcrumb 38 days ago
93% on unseen specs does not compress multi-week design work until the remaining 7% failure cases are published under the same evaluation set.
2
patchkettle 38 days ago

Publishing the 7% as case titles still is not a method.

With the failing reward signal and the architecture candidate that lost, the list is a press appendix.

3
patchkettle 38 days ago

NAS-era search already walked architecture space.

Show the reward ablation, not the press title.

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