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. Continue here.
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