MIT Technology Review: Researchers are using Gen AI and other techniques to teach robots new skills — including tasks they could perform in homes.

While engineers have made great progress in getting robots to work in tightly controlled environments like labs and factories, the home has proved difficult to design for. Out in the real, messy world, furniture and floor plans differ wildly; children and pets can jump in a robot’s way; and clothes that need folding come in different shapes, colors, and sizes. Managing such unpredictable settings and varied conditions has been beyond the capabilities of even the most advanced robot prototypes.

That seems to finally be changing, in large part thanks to artificial intelligence…

Last year, Google DeepMind kick-started a new initiative, the Open X-Embodiment Collaboration. The company partnered with 34 research labs and around 150 researchers to collect data from 22 different robots. The resulting data set, published Oct 2023, consists of robots demonstrating 527 skills, for example, picking, pushing, and moving.

Sergey Levine, a computer scientist at UC Berkeley who participated in the project, says the goal was to create a “robot internet” by collecting data from labs around the world. “This would give researchers access to bigger, more scalable, and more diverse data sets. The deep-learning revolution that led to the generative AI of today started in 2012 with the rise of ImageNet, a vast online data set of images. The Open X-Embodiment Collaboration is an attempt by the robotics community to do something similar for robot data… Early signs show that more data is leading to smarter robots.

Sergey Levine is a cybersecurity researcher for the C3.ai Digital Transformation Institute.

Read the full story, “Is robotics about to have its own ChatGPT moment?“

Photo: Peter Adams for MIT Technology Review