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Anyscale uses Ray to speed up JEPA robotics inference

Anyscale has developed a system using Ray to accelerate real-time inference for JEPA world model architectures in robotics. The V-JEPA2-AC model, previously capable of 65-80% success in pick-and-place tasks, suffered from slow planning times of up to 16 seconds per action. By offloading inference to a Ray cluster with more powerful GPUs like the NVIDIA A100, Anyscale has significantly reduced this planning time, enabling faster, continuous robot operation. AI

IMPACT Accelerates real-time inference for robotic control systems, enabling faster and more continuous operation.

RANK_REASON Anyscale blog post detailing an implementation using Ray for robotics inference.

Read on Anyscale blog →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

Anyscale uses Ray to speed up JEPA robotics inference

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Anyscale blog post detailing an implementation using Ray for robotics inference.
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COVERAGE [1]

  1. Anyscale blog TIER_1 English(EN) ·

    Real-time inference for JEPA world model architectures with Ray

    Scale JEPA world model planning with Ray on Anyscale, distributing inference across GPU clusters to accelerate robotic decision-making.