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AI in the physical world: humanoid robots, embodied foundation models, and action in real environments.

2 picksPast 30 days: 1 itemTotal: 91 items

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Embodied AI top picks

Sep 23WedItems 1–2
  1. Microsoft Research60

    Microsoft Research shows offloading robot AI inference improves performance and battery life

    Microsoft Research reports that running physical AI inference on onboard GPUs can limit robot performance and battery life, while offloading inference to edge or cloud GPUs improved results in mobile manipulation tests. In its evaluation, smaller onboard GPUs slowed mapping and planning by up to 383% compared with an A100, and large onboard GPUs such as Jetson Thor drained robot batteries by up to 160%.

    Why it matters: The study measures how offloading robot inference to edge or cloud GPUs changes task success, battery life, and model size, offering evidence for infrastructure design.

Aug 27Thu
  1. Anthropic · YouTube62

    Anthropic and HHMI Janelia launch Model Hardware Standard for AI lab equipment

    Anthropic is building the Model Hardware Standard (MHS), a common way for AI models to connect to lab and manufacturing equipment and operate it with safety limits built into each device. MHS started as a collaboration between Anthropic and HHMI Janelia Research Campus and is launching as a research preview with partners across science, robotics, and manufacturing.

    Why it matters: The source describes a standard for connecting AI models to lab and manufacturing hardware, which matters for anyone building automated experimentation workflows.