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2:06:16ZH → English
Zhang Xiaojun Podcast· Nov 28, 2025Podcast · 2 speakersTan Jie on Data Bottlenecks, Generalist Robots, and the Road to Real-World RoboticsGuest 谭捷 · Host 张小珺Google DeepMind robotics researcher Tan Jie traces his path from computer graphics to robotics and from reinforcement learning to Gemini Robotics. He argues that data scale and coverage, cross-embodiment transfer, real-time reasoning, and safety remain key to bringing robot foundation models into the real world.
2:49:35ZH → EnglishZhang Xiaojun Podcast· Feb 4, 2025Podcast · 2 speakersPan Jiayi on R1, o1, and Kimi K1.5: How Reinforcement Learning Teaches Models to ReasonGuest 潘嘉怡 · Host 张小珺Pan Jiayi, a Berkeley PhD student, walks through reasoning-model reports from DeepSeek, OpenAI, and Kimi, unpacking long chains of thought, GRPO, reward design, and distillation. R1-Zero’s “aha moment” shows how reasoning strategies can emerge through reinforcement learning.
1:27:02ZH → EnglishZhang Xiaojun Podcast· Sep 5, 2024Podcast · 3 speakersGuangmi: Self-Play RL Could Open a New Scaling Law for AGIGuest 广密 · Host 张小珺Guangmi believes the marginal gains from scaling language pretraining alone may be fading, making self-play reinforcement learning a more promising path. Whether it generalizes to coding, video, robotics, and beyond may determine the next stage of the AGI race.