This episode features an interview with Yao Shunyu @ShunyuYao14 , Research Scientist at Google DeepMind. Yao has held research scientist roles at both Anthropic and Google DeepMind, contributing to the development of key models including Claude 3.7, 4.5, and Gemini 3. Yao Shunyu is not your typical nerd. Every now and then, he’ll catch you off guard with a flash of irreverence. “None of the old guard are your relatives — so if you think someone’s being dumb, they’re just being dumb. Say it. No big deal.” (laughs) “Everyone’s a surfer now, but what really matters is the wave — not the person riding it.” “AI doesn’t actually require that much brainpower — I mean it genuinely doesn’t — most of this is work any undergrad could do. The most important quality in this industry is reliability: being meticulous, and taking responsibility for what you put out.” “You don’t need to worry too much about ruffling feathers with your opinions. As long as your views are internally consistent — not just taking random shots at people, but grounded in your own genuine understanding — there are objective standards for how you’re doing in this field. People will respect you for it.” Let us have a little fun with this one! 😄​​​​​​​​​​​​​​​​

Had a great time chatting with @zhang_benita on a bunch of agent-related topics: - history from the 40s to the present - the role of language - do world models need language? - world modeling vs. continual learning - the OpenClaw moment vs. the ChatGPT moment - and more Interview is a nice forcing function to organize thoughts

The era of large language models has moved past its first act—the chat era—and entered its second act: the age of Agents. On this show, we’ll dive deep into the core technical principles of Agents and break down the technology for you, offering a clear overview of its evolutionary trajectory. If you enjoy our show, we’d appreciate it if you could leave us a 5‑star rating on Apple Podcasts🤓🤓

Yes, our latest special guest is Fuli Luo @_LuoFuli . The second battle in the global large model arms race has begun: shifting from the Chat era dominated by pre-training to the Agent era driven by post-training. This marks Fuli Luo’s first-ever interview, as well as her first in-depth technical conversation. We talked systematically about the massive AI upheaval triggered by technological breakthroughs including Claude Opus 4.6 and OpenClaw in 2026, along with its subsequent structural impacts across the industry. Amid the fierce large-model arms race, the world around us is undergoing brutally rapid changes—even for researchers who train models firsthand. “I used to believe our work was highly creative, and could never be simplified into fixed skills or standardized workflows. But now I realize it can be automated after all. If that’s possible, can models train stronger models on their own? Can they achieve iterative improvement through self-evolution? This is exactly what will unfold in the next couple of years,” Fuli Luo says. As human knowledge and wisdom are internalized into model capabilities, what will humanity pursue in the future? Is our society truly ready for this tsunami-scale technological revolution? All in all, this is an information-dense dialogue. It reveals how an AI lab makes strategic technical bets, allocates resources, and adjusts organizational structure and team planning amid a major paradigm shift. At the core of its response to drastic change lies its established culture and core values. Though lengthy and technically intensive, we hope this conversation brings great insights to every viewer. Our podcast, video episode and article are released simultaneously across platforms, with English subtitles provided to assist non-Chinese-speaking audiences. Luo Fuli: OpenClaw, Agent Frameworks — The AI Paradigm Has Already Chang... 来自 @YouTube

Continuing to model the world through long-form podcasts! @CarinaLHong This episode is full of the "beauty of mathematics". She is also our youngest guest to date — Hong Letong, born in 2001, known online as the "Math Girl". This is her first-ever interview in Chinese. We talked about mathematics as invented versus discovered, proofs from the Book of Proofs, the entrepreneurial journey of the most unlikely founder, and of course, AI for Math. ✍🏻✍🏻 A 4-hour Interview with Carina Hong: AI for Math, Lean, Proofs from The ... 来自 @YouTube

Over the past three years (2023-2026), Guangmi and I have been documenting the evolution of global large language models through quarterly reports. This is Episode 9—stay tuned! "If you only listen to one podcast per quarter about global LLMs, make it this one."🙇🏻

i really like the way @sainingxie articulates his thoughts and builds elegant analogies around them. i’d strongly recommend watching the section of the podcast where he talks about research taste. one idea that stood out to me was his view that good research taste means being able to see through the illusions or superficial framing of a problem and uncover its true underlying substance. he connects this beautifully with philosophical ideas which makes the discussion even richer. i also really liked his analogy that great research is a lot like filmmaking or storytelling. btw thanks @eliebakouch for the recommendation!