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Zhang Xiaojun Podcast· Nov 28, 2025Podcast · 2 speakersTan Jie: Data Is the Bottleneck for General-Purpose Robot Intelligence, and a General Form Will Take TimeGuest 谭捷 · Host 张小珺Tan Jie, a robotics research scientist at Google DeepMind, looks back on his path from computer graphics to robotics, from reinforcement learning to Gemini Robotics. He argues that robot foundation models have not yet become an independent discipline, and that data scale and coverage, cross-embodiment transfer, real-time reasoning, and safety remain key to real-world applications.
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Berkeley PhD candidate Pan Jiayi 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 returns from scaling language pretraining alone may be diminishing, making self-play reinforcement learning a more promising path. Whether it generalizes to code, video, robotics, and beyond will shape the next stage of the AGI race.