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NVIDIA AI Introduces ASPIRE: A Self-Improving Robotics Framework Reaching 31% Zero-Shot on LIBERO-Pro Long Tasks

Traditional robot programming is hard to scale. It requires orchestrating multimodal perception, physical contact dynamics, diverse configurations, and execution failures by hand. Code-as-policy systems let language models compose these into executable robot programs. That makes robot behavior inspectable, editable, and debuggable. But existing robotic coding agents run in naive execution environments. They receive only coarse,…

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TurboQuant: Is the Compression and Performance Worth the Hype?

  #  Introduction   TurboQuant is a novel algorithmic suite and library recently launched by Google. Its goal is to apply advanced quantization and compression to large language models (LLMs) and vector search engines — indispensable elements of retrieval-augmented generation (RAG) systems — to improve their efficiency drastically. TurboQuant has been shown to successfully reduce…

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