Tutor Intelligence CEO Josh Gruenstein谈机器人估值逻辑
Josh Gruenstein of Tutor Intelligence on how to value a robot: "You take how much work a robot can d...
Tutor Intelligence 的 CEO 讲怎么给机器人定价:工作量除以成本,机器人每小时 16 美元进工厂干活,人远程教学攒数据,聊得挺实在。
Tutor Intelligence 联合创始人兼 CEO Josh Gruenstein 在 a16z 播客中提出机器人估值方法:用机器人能完成的工作量除以成本即可。该公司在马萨诸塞州制造机器人,按小时计费(如每小时 16 美元),无需前期投入,从首次销售电话到机器人上线约需三个月。当 AI 卡住时,人类远程接管并示范任务,同时生成训练数据。节目还引用华尔街对机器人年销量的预测:2026 年 2900 万台,2030 年 9300 万台,2050 年达 14 亿台。
Josh Gruenstein of Tutor Intelligence on how to value a robot: "You take how much work a robot can d...
Josh Gruenstein of Tutor Intelligence on how to value a robot: "You take how much work a robot can do and you divide it by its cost, and that's it. Everything else is commentary." If robots can do that work for less, he says the market is "all physical work done." One Wall Street firm's view of the scale, in a forecast of annual robot sales: - 2026: 29 million - 2030: 93 million - 2040: 605 million - 2050: 1.4 billion "We're just gonna have way more factories in the same way that we have way more businesses because the cloud and all of the software tooling let people build new businesses." "Anybody will be able to start a business in the physical world. Anybody will be able to scale a business in the physical world if we kind of have this infinite flexible labor substrate." @joshgruenstein @tutorintel a16z @a16z Tutor Intelligence co-founder and CEO Josh Gruenstein is putting AI robots to work in American factories and warehouses, taking on the back-breaking jobs they can't hire for. Tutor builds its robots in Massachusetts and charges by the hour, with no upfront cost. When the AI gets stuck, a human "tutor" takes over and teaches it the task, creating training data along the way. Josh joins a16z's Martin Casado and Raghu Raghuram to discuss how Tutor goes from a first sales call to a working robot in about three months, why so many robot startups died building for a single customer, why anyone will be able to start a business in the physical world, and a whole lot more. 0:50 Deploy robots, then build the data 2:50 Why smart robots aren't enough 4:38 The ultimate systems problem 6:45 Why robot companies go vertical 9:07 How remote humans tutor robots 11:00 Will robots outgrow their tutors? 14:54 How AI labs sped up robotics 16:57 Meet Cassie and Sonny 20:55 What factory work actually looks like 23:18 A robot for $16 an hour 25:51 When robots become coworkers 29:04 Why robot startups keep dying 31:21 When 1% cheaper flips a market 34:52 Robots cost more to run than to buy 38:18 China's automation bet may backfire 42:02 Real-world RL on a 100-robot fleet YouTube: youtu.be/lXkjXSul6yg @joshgruenstein @tutorintel @martin_casado @RaghuRaghuram Your browser does not support the video tag. 🔗 View on Twitter 🔗 View Quoted Tweet 💬 13 🔄 9 ❤️ 76 👀 14773 📊 17 ⚡