kalomaze: fluid generalization is composing independent skills across domains end-to-end
kalomaze · x · 2026-09-07
kalomaze proposes a conceptual model of deep transfer learning: fluid generalization across domains is primarily a function of needing to compose independent skills from distinct domains together in an end-to-end compositional process. If you're trained on real-world skills, every weird problem unlike any professional playbook becomes a bottleneck — so models should generalize over a broader compositional space of constraints, even unrealistic ones, since specific environments rarely exercise this skill composition.
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