Josh Gruenstein × Martin Casado × Raghu Raghuram

Hand-assembled iPhone packaging illustrates Gruenstein’s claim that nine of ten US factories and warehouses lack robots.Tutor’s $16-an-hour offer requires no upfront customer CapEx; contracts take 40–60 days and deployment about 40 more, Gruenstein says.Paid work builds its data loop, but ongoing costs now exceed hardware costs, making inference, teleoperation and reliability central economic tests.

曲凯 × 王淏楠

Astra把大模型视觉理解转为物理动作，商业价值仍待真实场景验证。淏楠设想小模型成功率达50%—60%后由GPT接管失败、沉淀恢复数据，或推至80%，使一人遥操十台机器。创业壁垒在硬件与System协同设计和真机采数，酒店叠被子是落地例子。

钱程 × 张小珺

接班暴露的关键风险不是战略方向，而是组织承接：国内与海外整合如“油和水”，个人洞察未能沉淀为组织能力。全球化仍是明确下注，海外收入占比已达50%，钱程预计未来几年到60%、70%；多品类扩张须匹配技术、渠道与规模，具身家庭应用可能还需5—10年。

泓君 × 朱哲清 × 王晟 × 许华哲

Astra登顶RoboDojo等机器人基准，许华哲称其为定性跃迁，但速度慢、缺直觉物理，仍需更小更快的专用模型；他预计通用机器人或于2028年初实用。消费级Agent受成本和访问权限制，Astra价格为GPT-6-4的四至五倍，商家也屏蔽云端IP。

John Collison × Chris Sacca × Will O'Brien

Ulysses’ Mako can sell for as little as $50,000 to navies versus roughly $5 million for the common U.S.Navy autonomous underwater vehicle, while Leviathan supports persistent, modular missions.Demand already exceeds manufacturing capacity, with a factory planned next year; slow procurement could become a moat once deployments make undersea monitoring sticky and bankable.

Lindon Gao × 张小珺

Dyna不再扩张已有十余客户的折叠业务：补料停机暴露任务完成不等于商业闭环，转而让research围绕完整工作流推进。百万小时级ego-centric预训练出现“非常强的scaling law”，酒店洗衣房成为B2B首站；Lindon称美国10万家酒店对应数十亿美元TAM，规模化产品价值仍需一到两年。

swyx × Jason Ma × Vibhu

Multi-site deployments folding thousands of napkins daily at Din Tai Fung and laundry for Best Western offer commercial proof beyond pilots; Din Tai Fung has signed a much bigger contract.Jason calls Dyna-2 the first world action model trained on more than 1 million hours of data, but missing sensing modalities remain a potential constraint on broader generality.

swyx × Brandon × Liam Fedus × Ekin Dogus Cubuk

Periodic’s differentiated asset is timestamped lineage across failed experiments, computations, instrument data, code, discussions, and successes, enabling models to learn scientific process rather than published endpoints.Its AI-simulation-experiment loop targets automated characterization, with secure on-site semiconductor deployment as the near-term wedge, while the longer-term “matter compiler” faces unknown physical variables and difficulty discovering superconductors without a complete theory.

swyx × Brandon × Liam Fedus × Ekin Dogus Cubuk

Periodic Labs is building AI, simulations, and high-throughput physical labs as a closed loop, with timestamped failures, instrument data, and campaign lineage potentially differentiating its scientific intelligence.Automated characterization—not humanoid robotics—is the near-term bottleneck, while secure on-site deployments for semiconductor companies could evolve from Copilot-style assistance toward outcome pricing; whether throughput can compress discovery without better physical representations remains the key risk.

卫诗婕 × 熊友军

人形机器人运动会正从速度竞赛转向自主化与具身智能验证场，天工 Omni 从彩排9秒44迭代至8秒64，“无脸跑”则是在肩关节和功耗约束下自我学习出的最快解。商业化仍受7×24小时运行、甚至99%成功率的工业门槛约束，工业场景将先提供收入与数据，但长程规划、错误反思、数据规模和人形终局仍是待验证变量。