100. 对话奔驰全球CEO康林松：转型期CEO和转型之中的139岁奔驰
El artículo aún no está listoTenemos los datos de este vídeo, pero su artículo todavía no se ha escrito. Mientras tanto puedes verlo en YouTube.Abrir en YouTube
Más de este canal
1:59:52EN
Zhang Xiaojun Podcast· 21 oct 2026Pódcast · 2 vocesDavid Qian on Succession, Robotics, and Finding His Own AmbitionInvitado: David Qian (Qian Cheng) · Presenta: 张小珺Ecovacs CEO David Qian reflects on inheriting a founder-built company, learning to lead through mistakes, and choosing a patient path in robotics. His account treats succession as an ongoing effort to build the company for a new era, not a finish line.
2:51:18ENZhang Xiaojun Podcast· 15 oct 2026Pódcast · 2 vocesLindon Gao on Building Dyna Robotics and Finding a Path Through the FogInvitado: Lindon Gao · Presenta: 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.
2:34:18ENZhang Xiaojun Podcast· 3 sept 2026Pódcast · 2 vocesZeng Ming on AI’s New Era: Why Great Companies and New Organizations EmergeInvitado: Zeng Ming · Presenta: 张小珺Zeng Ming argues that AI is changing the foundations of business: models will become infrastructure, while new Agent-native applications and organizations create the next wave of value. His advice to founders is to embrace uncertainty, rethink strategy continuously, and build around meaningful work rather than inherited structures.
2:34:18ZHZhang Xiaojun Podcast· 3 sept 2026Pódcast · 2 voces曾鸣：AI 产业化的三阶段与公司组织的消亡Invitado: 曾鸣 · Presenta: 张小珺战略学者曾鸣以互联网、工业革命和电气化的历史周期为参照，提出 AI 正从基础设施走向 Agent 应用，并最终进入原生应用阶段。他认为，旧公司的科层制难以穿越范式转型，下一代组织将围绕任务、创造力和人机协同重构。
46:26ZHZhang Xiaojun Podcast· 9 dic 2025Pódcast · 2 voces朱啸虎：三年内看不到泡沫，共识太集中就错开十五度Invitado: 朱啸虎 · Presenta: 张小珺2025 年底，金沙江创投朱啸虎第三次坐到张小珺对面：AGI 不谈了，入口之争开始了。他不投人形机器人，把支票开给洗船和按摩这类「干活」的公司。
2:06:16ZHZhang Xiaojun Podcast· 28 nov 2025Pódcast · 2 voces谭捷：机器人通用智能的瓶颈在数据，通用形态仍需时间Invitado: 谭捷 · Presenta: 张小珺Google DeepMind 机器人研究科学家谭捷回顾了从计算机图形学到机器人、从强化学习到 Gemini Robotics 的研究路径。他认为机器人基础模型尚未成为独立学科，数据规模与覆盖度、跨本体迁移、实时推理和安全仍是走向真实应用的关键。