Occamy-1.0: Teaching a 35B Agent to Finish the Job
Introduces a 35B cost-efficient model positioned at the Pareto frontier for collaborative long-horizon agent tasks, achieving performance competitive with significantly larger systems. Advances the capability of embodied and agentic AI to handle extended multi-step cooperative workflows. In this episode of Embodied AI 101, we explore "Occamy-1.0: Teaching a 35B Agent to Finish the Job". We break down the research, methodology, and real-world implications for robotics, AI, and physical intelligence. Embodied AI 101 covers the latest research at the intersection of AI and physical intelligence…
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