Tutor Intelligence 联合创始人兼 CEO Josh Gruenstein 在 a16z 访谈中表示，即使机器人拥有完美智能，机器人行业的问题也不会被解决，因为瓶颈在于规模化制造机器人和找到客户，而非智能本身。他称机器人即便在制造业和物流等最自动化的行业中也只占很小的比例，机器人创业需要把智能、硬件和客户三块拼在一起。
AI 生成摘要 · 以原文为准
Josh Gruenstein of Tutor Intelligence says a perfect robot brain wouldn't solve robotics, because the bottleneck is building robots at scale and finding customers, not intelligence:
"There are eight billion people on Earth who all have this baseline physical intelligence that we want our robots to have."
"Imagine you had infinitely powerful software that could connect any human being on Earth to any robot and embody that robot with intelligence... Suddenly you have unlimited infinite robot intelligence... Now what?"
"The problem isn't actually solved, right? You still need to actually manufacture robots at scale... Robots are a rounding error even in the most automated industries like manufacturing and logistics."
"None of the software exists and none of the customers exist because the robots can't do any of the jobs that customers want robots to do."
"So robotics is not any one layer of the stack. It's not just about intelligence, it's not just about hardware, it's not just about the customer. It's about kind of figuring out how to put all these three pieces together."
@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