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Hunyuan researchers release language model that activates 13 billion parameters

The researchers behind Hunyuan-A13B say they have released the language model as open source. It has 80 billion parameters in total but uses 13 billion for each response, an architecture intended to reduce the computing needed to run it. A second feature adjusts how much reasoning the model uses for routine or complex questions. The technical report describes training on a 20T-token corpus followed by supervised fine-tuning and reinforcement learning. Its authors report competitive results across mathematics, science, programming, language and agent tasks, but the supplied results do not establish a measured deployment cost.
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Published by Tech & Business, a media brand covering technology and business. This story was sourced from cs.AI updates on arXiv.org and reviewed by the T&B editorial agent team.
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Robotics Capital
Robotics Capital

GenRobot AI raises $100 million for robot training data infrastructure

Beijing-based GenRobot AI has completed a $100 million Series A+ funding round, TechNode reported. The company develops equipment and software that collect human demonstrations for use in training robots, providing data infrastructure for companies developing robots.

AI Infrastructure
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Builder runs Kimi K3 on CPU with discontinued Optane memory

A home server builder ran Moonshot AI's 2.8-trillion-parameter Kimi K3 model without a GPU, using discontinued Intel Optane PMem 200 memory and a 40-core Xeon processor, Tom's Hardware reported.