While the capabilities of robots have improved significantly over the past decades, they are not always able to reliably and ...

Researchers at Los Alamos National Laboratory have developed a new approach that addresses the limitations of generative AI ...

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 ...

Diffusion models gradually refine and produce a requested output, sometimes starting from random noise—values generated by the model itself—and sometimes working from user-provided data. Think of ...

(Nanowerk News) A new, potentially revolutionary artificial intelligence framework called “Blackout Diffusion” generates images from a completely empty picture, meaning that the machine-learning ...

It’s hard to ignore the buzz around artificial intelligence these days. Whether it’s the promise of smarter virtual assistants, robots that can perform backflips, or AI models that churn out lifelike ...

Nvidia released a comprehensive robotics ecosystem at CES 2026, combining open foundation models, simulation tools, and edge hardware in a bid to become the default platform for generalist ...

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 ...

Deep neural networks based on self-attention are revolutionizing robotics with their ability to perform "open world" reasoning across multiple modalities including text and images, and their ability ...

Three different data domains — simulation (top), robot tele-operation (middle) and human demos (bottom) — allow a robot to learn to use different tools. CAMBRIDGE, MA – Let’s say you want to train a ...