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Westlake Robotics, incubated by Westlake University, has unveiled the humanoid robot Titan o1, powered by the world’s first motion generalization large model. Breakthrough Technology Demonstration Highlights Titan o1’s futuristic orange-black-silver design was paired with motion capture. When a staff member waved, turned, or kicked a ball, Titan o1 replicated every detail—arm angles, turning range, stride length, and rhythm—with millisecond precision. Ease of Use No programming skills required. With motion capture gear or simple computer input, users can make robots execute corresponding actions—“what you think is what they do.” Technical Edge Real-World Potential Beyond “cyber avatars,” Titan o1 could replace humans in high-risk environments such as firefighting, mining, or high-altitude maintenance, opening new horizons for practical deployment. This marks a milestone:...

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This afternoon, Huawei officially launched the Enjoy 90 series, bringing Kirin chips and the latest HarmonyOS to the budget smartphone segment. Lineup Strategic Significance Statement from Yu Chengdong Although absent from the launch due to health reasons, Huawei’s Terminal BG Chairman Yu Chengdong posted: “Today, with the release of the Enjoy 90 series powered by Kirin chips and HarmonyOS, Huawei smartphones have truly achieved a full return!” This marks Huawei’s re-entry into the budget market, reinforcing its presence across the entire smartphone spectrum.

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NVIDIA researchers have introduced a breakthrough compression technology called KVTC (KV Cache Transform Coding), designed to dramatically reduce the memory footprint of large language models (LLMs) during long conversations. Key Highlights Why It Matters Industry experts believe KVTC could become as standard as video compression, enabling AI systems to handle ever-longer conversations efficiently and at scale.

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In recent years, the focus of AI has shifted from training to inference, and NVIDIA is aiming to reshape this space with its newly announced LPU (Language Processing Unit) chips at last week’s GTC conference. During the event, NVIDIA’s Chief Scientist Bill Dally sat down with Google’s Chief Scientist Jeff Dean for a deep technical discussion. Dally highlighted that the real bottleneck in AI inference today isn’t raw compute power—it’s communication overhead. This leap would represent a massive acceleration in AI responsiveness, making real-time, high-throughput inference practical for everyday use.

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