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The Robot Report

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Meta V-JEPA 2 world model uses raw video to train robots

  • Meta introduced V-JEPA 2, a 1.2-billion-parameter world model trained on video for robotic systems.
  • V-JEPA 2 aids robots in understanding, prediction, and planning tasks with limited training data.
  • The model goes through a two-stage training process without human annotation, learning from over 1 million hours of video.
  • Meta tested V-JEPA 2 on robots in its labs, performing well on tasks like pick-and-place.
  • The model uses vision-based goal representations and visual subgoals for complex tasks.
  • In tests, V-JEPA 2 showed promising ability to generalize to new environments, with success rates of 65-80%.
  • Despite improvements, Meta notes a gap between model and human performance.
  • Meta suggests the need for models operating across timescales and modalities like audio or tactile information.
  • Meta releases benchmarks to evaluate models' physical understanding from video.
  • V-JEPA 2 code and model checkpoints are available for commercial and research use to promote exploration in robotics and AI.
  • Other tech companies like Google DeepMind and World Labs are also developing their own world models.
  • Google DeepMind's Genie simulates 3D environments, while World Labs raised $230 million for world model development.

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