Self-distillation from production traces could make models improve with use
ypatil125 · x · 2026-08-04
The post argues that models should improve with use by learning from real production traces.
- It frames self-distillation as a way to pull meaningful signal from user feedback that usually never reaches training pipelines.
- The core claim is that training and inference are becoming increasingly intertwined rather than separate stages.
- It also says AC2 now has native support for OPSD and RMSD, and shares a preview of the integration.
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