MIT researchers developed a technique to combine robotics training data across domains, modalities, and tasks using generative AI models. They create a combined strategy from several different ...

Essentially, where Large Language Models (LLMs) like ChatGPT can ingest billions of words of human writing, and teach themselves to write and code – and even reason, for god's sake – at a level ...

The study of natural and artificial intelligence in physical agents has a great interest both from a scientific and technological point of view. On the one ...

Robots are getting better at sensing their surroundings, but moving safely through unfamiliar spaces remains a bottleneck. Most autonomous systems still depend on building detailed maps, fusing ...

This efficiency makes it viable for enterprises to move beyond generic off-the-shelf solutions and develop specialized models ...

Russ Tedrake likes to present an eye-opener looking into what's possible now with robotics, and what is likely to be possible in the near future, as we see AI robots vault into our lives. “This is a ...

Packing the car for a road trip might seem like a straightforward enough task, but it’s never been an easy one for robots to learn—until a new study turned the robot training over to artificial ...

Training robots to execute tasks in the real world requires data — the more, the better. The problem is that creating these datasets takes a lot of time and effort, and methods don’t scale well.

Robots have gotten exceptionally good at specialized tasks—vacuuming floors, stacking boxes, welding parts, or navigating controlled warehouses. Yet the dream ...