MIT Technology Review September 20, 2024
Rhiannon Williams

“Robot utility models” sidestep the need to tweak the data used to train robots every time they try to do something in unfamiliar settings.

It’s tricky to get robots to do things in environments they’ve never seen before. Typically, researchers need to train them on new data for every new place they encounter, which can become very time-consuming and expensive.

Now researchers have developed a series of AI models that teach robots to complete basic tasks in new surroundings without further training or fine-tuning. The five AI models, called robot utility models (RUMs), allow machines to complete five separate tasks—opening doors and drawers, and picking up tissues, bags, and cylindrical objects—in unfamiliar environments with a 90% success rate.

The...

Today's Sponsors

LEK
ZeOmega

Today's Sponsor

LEK

 
Topics: AI (Artificial Intelligence), Robotics/RPA, Technology
The case for human-centered AI
European Commission Approves Nvidia’s Proposed Acquisition of Run:ai
How Health Systems Can Collaborate on AI Tools
The Future Talent Equation: How To Identify And Retain Talent In The Age Of AI
A Roadmap For AI In Education: Turning Disruption Into Opportunity

Share This Article