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#217 – Rodney Brooks: Robotics

#217 – Rodney Brooks: Robotics

Lex Fridman Podcast XX

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Full Transcription:

[0] The following is a conversation with Rodney Brooks, one of the greatest roboticists in history.

[1] He led the computer science and artificial intelligence laboratory at MIT, then co -founded I -Robot, which is one of the most successful robotics companies ever.

[2] Then he co -founded Rethink Robotics that created some amazing collaborative robots like Baxter and Sawyer.

[3] Finally, he co -founded Robust .a .I., whose mission is to teach robots, common sense.

[4] which is a lot harder than it sounds.

[5] To support this podcast, please check out our sponsors in the description.

[6] As a side note, let me say that Rodney is someone I've looked up to for many years in my now over two -decade journey in robotics because, one, he's a legit, great engineer of real -world systems, and two, he's not afraid to state controversial opinions that challenge the way we see the AI world.

[7] But of course, while I agree with him on some of his critical views of AI, I don't agree with some others.

[8] And he's fully supportive of such disagreement.

[9] Nobody ever built anything great by being fully agreeable.

[10] There's always respect and love behind our interactions.

[11] And when a conversation is recorded like it was for this podcast, I think a little bit of disagreement is fun.

[12] As usual, I'll do a few minutes of ads now, no ads in the middle.

[13] I try to make these interesting, so hopefully you don't skip, but if you do, please still check out the sponsor links in the description.

[14] It is the best way to support this podcast.

[15] I use their stuff and enjoy it.

[16] Maybe you will too.

[17] This show is brought to you by PaperSpace Gradient.

[18] These guys are amazing.

[19] It's a platform that lets you build, train, and deploy machine learning models of any size and complexity.

[20] I love how powerful and intuitive it is.

[21] I'm likely going to use PaperSpace for a couple of machine learning.

[22] experiments I'm doing as part of an upcoming video.

[23] Fast