How Robots Learn: Much Slower Than Humans At First, Then Infinitely Scalable
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Episode Description
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Brief Summary
Humans learn quickly while robots need more data; once learned, robots can share skills instantly.
Key points
- The Snowball Effect. Things are improving rapidly, like a snowball gaining momentum down a hill.
- Human Learning vs. Robot Learning. Humans learn quickly with little data, while robots require much more.
- Robots and Shared Knowledge. Once one robot learns a skill, all of its type can replicate it.
Transcript
I don't believe that there's this singularity. I do believe that things are going to get better and better. Think of it more like a snowball picking up steam going down a hill. Got it? >> But the reason that it's snowballing like this is because people are putting money and resources and engineering time and engineering effort in as they explore everything and start to figure all of this stuff out. Humans, for example, we've evolved to learn. We are very good at learning and it takes very little data to show us how to do something and then we practice and practice and iterate. Robots are not very good at learning yet. Robots take
so much more data. so many more examples at a person. We're still figuring out how to teach robots how to learn. But then one of the benefits that robots have in the long run is they've got Wi-Fi. You know, when you learn how to play the violin, you can't just load that to somebody else and then they learn how to play the vi know how to play the violin based on your learnings. Robots will be >> one robot learns to play violin. All robots know how to play a violin >> or all robots of that type know how to play the violin, right? And then minor variations for the next type in the next piece of hardware.
