In a new paper published online Aug. 27 in the journal Science Robotics, Berkeley professor and robotics expert Ken Goldberg describes how what he calls the “100,000-year data gap” will prevent robots from gaining real-world skills as quickly as AI chatbots are gaining language fluency.
In a second article, leading roboticists from MIT, Georgia Tech and ETH-Zurich summarize the heated debate among roboticists over whether the future of the field lies in collecting more data to train humanoid robots or relying on “good old-fashioned engineering” to program robots to complete real-world tasks.
“We’re all very familiar with ChatGPT and all the amazing things it’s doing for vision and language, but most researchers are very nervous about the analogy that most people have, which is that now that we’ve solved all these problems, we’re ready to solve [humanoid robots], and it’s going to happen next year,” said Goldberg.
“I’m not saying it’s not going to happen, but I’m saying it’s not going to happen in the next two years, or five years or even 10 years. We’re just trying to reset expectations so that it doesn’t create a bubble that could lead to a big backlash."
Read more in Berkeley News: Are we truly on the verge of the humanoid robot revolution?
