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  10. UCSD Hao AI LabSelected

    Hao AI Lab releases the ORA open-source robot agent framework, powered by DeepSeek-V4.1-Flash

    Hao AI Lab releases the ORA (Open Robot-Use Agents) open-source framework, powered by DeepSeek-V4.1-Flash, which operates robots zero-shot from visual input without VLA and can compete with frontier model agents. ORA achieves 69.2% on RoboTwin and 81.4% on LIBERO-Pro; by comparison, RPent achieves 62.4%/58.4% on RoboTwin (GPT-5.5/Opus-4.7) and 82.4% on LIBERO-Pro (Opus-4.7). It works similarly to a coding agent, completing the loop through prompts, perception and action tools, and context management; the same framework can run ARX X5, ALOHA, and Franka, with a model cost of about $0.30–0.35 per solved case. In preliminary real-robot tests, DeepSeek-V4.1-Flash used a low-cost robotic arm, a fixed RGB-D camera, and a wrist camera to pull open a drawer handle and put candy into a box.

    Hao AI Lab releases the ORA (Open Robot-Use Agents) open-source framework, powered by DeepSeek-V4.1-Flash, which operates robots zero-shot from visual input without VLA and can compete with frontier model agents. ORA achieves 69.2% on RoboTwin and 81.4% on LIBERO-Pro; by comparison, RPent achieves 62.4%/58.4% on RoboTwin (GPT-5.5/Opus-4.7) and 82.4% on LIBERO-Pro (Opus-4.7). It works similarly to a coding agent, completing the loop through prompts, perception and action tools, and context manage

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    #lab#English text is being prepared.#Embodied AI#Agents
  14. Rohan PaulSelected

    Meta open-sources 816B-parameter model Muse Spark Open on Hugging Face

    Meta has released the model weights of Muse Spark Open on Hugging Face, an 816B-parameter model aimed at coding and agent tasks. The open-source version shares the same base model as Muse Spark 1.3, with additional safety post-training to reduce the risk of misuse when used standalone without system guardrails, reversing Meta's strategy of its first proprietary closed frontier model in April this year. The model has 62 layers, each containing 256 expert networks, with each token routed to 8 of them, so deployment requires the memory of an 816B-parameter model but runs at the speed of a 42B model. A 3-bit quantized version tested on a 512GB M3 Ultra occupies about 344 GB, with generation speed of about 21 tok/s under short prompts.

    Meta has released the model weights of Muse Spark Open on Hugging Face, an 816B-parameter model aimed at coding and agent tasks. The open-source version shares the same base model as Muse Spark 1.3, with additional safety post-training to reduce the risk of misuse when used standalone without system guardrails, reversing Meta's strategy of its first proprietary closed frontier model in April this year. The model has 62 layers, each containing 256 expert networks, with each token routed to 8 of t

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    #ai-news#Model releases#Open-source ecosystem#English text is being prepared.