DeepMind's SkillSmith: Transforming Model Weights into Composable Skill Modules
eyishazyer · x · 2026-08-03
A new paper from Google DeepMind suggests that model weights do not have to remain static artifacts that can only be fine-tuned or averaged.
The proposed SkillSmith framework treats prefix key-value caches as another input modality. By interleaving existing prefix weights with task descriptions and examples, the system can initialize new capabilities from what the agent previously learned—marking a shift from learning isolated skills to composing them.
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