Tutor Intelligence 联合创始人兼 CEO Josh Gruenstein 在 a16z 播客中表示，人们想象中的无人化工厂只是美国制造物流的最顶端 0.01%，大量百万平方英尺设施仍靠人工在传送带和折叠桌旁手工操作。他称这类体力活极难招工，从业者平均年龄 55 岁且面临退休，甚至 iPhone 在最大规模下也是人工完成包装装盒。
AI 生成摘要 · 以原文为准
Josh Gruenstein of Tutor Intelligence says the machine-run factory most people picture is just the top .01%, and humans still box almost everything you buy:
"Most people have this mental picture of what the industrial base or manufacturing logistics looks like in the United States... You see these Rube Goldbergian machines of levers, and you don't see any humans in those pictures, right?"
"That's the top .01% of American manufacturing logistics. What's below that? You walk into these million square foot facilities and you see a bunch of people standing around on conveyor belts or folding tables doing things by hand."
"It's kind of shocking for anybody who doesn't come from this industry and community."
"A huge amount of work, which is back-breaking work that's really hard to hire for. There's a three-month turnover where your average age of the worker doing that work is 55 years old and about to retire."
"Basically anything you ever bought that came in a box, a human had to put that in a box, which is a crazy revelation for most people... Even iPhones, you would assume it's a robot putting that packaging together. No, it's a person even at the highest level of scale."
@joshgruenstein @tutorintel
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: https://youtu.be/lXkjXSul6yg @joshgruenstein @tutorintel @martin_casado @RaghuRaghuram在 X 查看被引用的帖子
来源：a16z · x.com