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Tuesday

  13. a16z：News

    a16z Leads Eka Robotics Series A Funding

    a16z announced it has led the Series A funding round of Eka Robotics, betting on its approach to solving the challenge of robotic dexterous manipulation. Eka builds a Vision-Force-Action model that combines visual perception with robotic hand force feedback, and trains manipulation policies with reinforcement learning in physical simulation, enabling robots to obtain information from contact itself and correct in real time when slipping or insertion is obstructed. The founding team includes Pulkit Agrawal of MIT CSAIL and Tuomas Haarnoja, co-proposer of Soft Actor-Critic.

    a16z announced it has led the Series A funding round of Eka Robotics, betting on its approach to solving the challenge of robotic dexterous manipulation. Eka builds a Vision-Force-Action model that combines visual perception with robotic hand force feedback, and trains manipulation policies with reinforcement learning in physical simulation, enabling robots to obtain information from contact itself and correct in real time when slipping or insertion is obstructed. The founding team includes Pulk

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    #analysis#Industry news#Embodied AI#English text is being prepared.

Wednesday

  5. PyTorch BlogSelected

    Google and Meta jointly launch TorchTPU, enabling PyTorch to run natively on TPUs

    Google and Meta's PyTorch teams have collaborated to launch the open-source project TorchTPU, providing a native PyTorch backend for Google TPUs; migration only requires changing model.to("cuda") to model.to("tpu"). The project supports both eager and torch.compile modes, adds a new DeferAndFuse eager mode, covers about 450 Aten operators, and has been verified to run out of the box on 4,917 Hugging Face models, with a Tier 1 pass rate of 98% and Tier 2 numerical consistency relative to GPUs of 97%. According to the official announcement, it has already been used in the inference and training production workloads of some major Google Cloud customers, and is integrated with vLLM, SGLang, TorchTitan, Ray, and TorchRec.

    Google and Meta's PyTorch teams have collaborated to launch the open-source project TorchTPU, providing a native PyTorch backend for Google TPUs; migration only requires changing model.to("cuda") to model.to("tpu"). The project supports both eager and torch.compile modes, adds a new DeferAndFuse eager mode, covers about 450 Aten operators, and has been verified to run out of the box on 4,917 Hugging Face models, with a Tier 1 pass rate of 98% and Tier 2 numerical consistency relative to GPUs of

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    #engineering#Product updates#Open-source ecosystem#English text is being prepared.