Ornith-1.5-122B Uses End-to-End Self-Improvement via Reinforcement Learning
October 20, 2026
Ornith-1.5-122B evolves the self-improvement loop by jointly optimizing task generation, scaffold construction, and solution rollouts. This approach moves beyond fixed human-curated datasets by using reinforcement learning to discover new training tasks and solving strategies.
HOW THIS AFFECTS YOU
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researcherYou can study how joint optimization of task generation and rollouts improves model policy stability and capability.