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WAMJET is an agentic harness that accelerates WAM inference by equipping coding agents with reusable optimization guidance and measurement and validation tools, and iteratively refines the acceleration stack as bottlenecks shift, while preserving action quality.
Factory work is a promising early scenario for embodied AI: assigning repetitive manual jobs to robots has clear economic payoff, and a structured station keeps the jobs tractable for current policies. Vision-Language-Action (VLA) models now dominate as the policy paradigm for these robots. The inference latency of VLA...
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