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2:51:18EN
Zhang Xiaojun Podcast· Oct 15, 2026Podcast · 2 speakersLindon Gao on Building Dyna Robotics and Finding a Path Through the FogGuest Lindon Gao · Host 张小珺Dyna Robotics CEO Lindon Gao explains why his company builds intelligence through real workflows, how hardware and research must evolve together, and how a founder can find clarity by letting go of the need to be right.
2:59:03ENZhang Xiaojun Podcast· Jul 28, 2026Podcast · 2 speakersYou Kaichao on How vLLM Grew from Open-Source Project to AI Infrastructure CompanyGuest You Kaichao · Host 张小珺Inferact co-founder You Kaichao traces vLLM’s path from Berkeley research to a company, then explains why model, inference, hardware and agent design increasingly have to move together.
3:46:12ENZhang Xiaojun Podcast· Jul 16, 2026Podcast · 2 speakersKay Ke on Physical Intelligence, Robot Learning, and the Future of RoboticsGuest Kay Ke · Host 张小珺Physical Intelligence researcher Kay Ke traces the field's research lineages and explains Pi's progression from π₀ to π*₀.₆. She also reflects on education, fiction, ambition, and what it means to build robots that work beyond a demo.
2:29:41ZH → EnglishZhang Xiaojun Podcast· Apr 7, 2025Podcast · 4 speakersChen Jianyu: How Robot Foundation Models Can Become General-Purpose VLA SystemsGuest 陈建宇 · Host 张小珺From SayCan and RT-2 to Diffusion Policy, Tsinghua assistant professor and Epoch Robotics founder Chen Jianyu traces the path from borrowing language models to end-to-end VLA. The hard problems remain diverse data, cross-embodiment generalization, and high-frequency action control.
2:36:13ZH → EnglishZhang Xiaojun Podcast· Feb 24, 2025Podcast · 2 speakersSonglin Yang on New Attention Papers from DeepSeek, Kimi, and MiniMaxGuest Songlin Yang（松琳） · Host 张小珺From dynamic sparse attention to hybrid linear-attention architectures: how three approaches to long context balance training, inference, and hardware efficiency.
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.
1:27:13ZH → EnglishZhang Xiaojun Podcast· Dec 29, 2024Podcast · 2 speakers李想: Cars Will Evolve from Transportation into Spatial RobotsGuest 李想 · Host 张小珺理想汽车 CEO 李想 explains why the company is moving from carmaking toward AI: foundation models are an operating system for the AI era, and cars are a way into the physical world. For him, the technology must deliver better experiences, capability and lasting value.
1:33:07ZH → EnglishZhang Xiaojun Podcast· Aug 17, 2024Podcast · 2 speakersLi Guangmi on a Year in Global LLMs: Scaling Law, the AGI Bet, and the US–China LandscapeGuest 李广密 · Host 张小珺Drawing on his front-row view from Silicon Valley, Shixiang Capital founder Li Guangmi looks back at the competition among OpenAI, Anthropic, Google, and Chinese model companies. He argues that model capability and cost together will shape the next wave of applications, while today’s enormous investments are bets on whether intelligence can keep scaling and how AI will reshape the economy and industry over the long term.
49:41ZH → EnglishZhang Xiaojun Podcast· Aug 17, 2024Podcast · 3 speakersFu Sheng: Large Models Are a Productivity Revolution, and Robots Have a New Window of OpportunityGuest 傅盛 · Host 张小珺Fu Sheng sees the heart of large models in their capacity for logic and reasoning. Their impact, he says, is closer to the steam engine than to another round of ordinary internet evolution. He also reflects on open models, service robots, and how entrepreneurs can face difficult periods.