Despite decades of progress, most robots are still programmed for specific, repetitive tasks. They struggle with the unexpected and can't adapt to new situations without painstaking reprogramming. But what if they could learn to use tools as naturally as a child does by watching videos?

Over the past decades, computer scientists have developed many computational tools that can analyze and interpret images. These tools have proved useful for a broad range of applications, including robotics, autonomous driving, health care, manufacturing and even entertainment.

From the voice-to-text feature on your phone to the captions that make videos more accessible, speech transcription is already woven into everyday life. Behind the scenes, artificial intelligence is doing the heavy lifting, transforming the spoken word into text with speed and accuracy that once seemed impossible.

A British woman suffering from motor neuron disease who lost her ability to speak is once again talking in her own voice thanks to artificial intelligence and a barely audible eight-second clip from an old home video.

Altruism, the tendency to behave in ways that benefit others even if it comes at a cost to oneself, is a valuable human quality that can facilitate cooperation with others and promote meaningful social relationships. Behavioral scientists have been studying human altruism for decades, typically using tasks or games rooted in economics.

Dr. Abolfazl Karimpour, Assistant Professor of Transportation Engineering at SUNY Polytechnic Institute and Director of the Transportation AI Research Lab (TRAIL), is lead author of a new study that advances understanding of e-scooter mobility in urban environments.

Google will provide its Gemini artificial intelligence tools to US federal agencies practically free, the government announced Thursday.

Machine learning software helps agencies make important decisions, such as who gets a bank loan or what areas police should patrol. But if these systems have biases, even small ones, they can cause real harm. A specific group of people could be underrepresented in a training dataset, for example, and as the machine learning (ML) model learns that bias can multiply and lead to unfair outcomes, such as loan denials or higher risk scores in prescription management systems.

With the particular needs of scientists and engineers in mind, researchers at the Department of Energy's Pacific Northwest National Laboratory have co-designed with Micron a new hardware-software architecture purpose-built for science.

At UC Berkeley, researchers in Sergey Levine's Robotic AI and Learning Lab eyed a table where a tower of 39 Jenga blocks stood perfectly stacked. Then a white-and-black robot, its single limb doubled over like a hunched-over giraffe, zoomed toward the tower, brandishing a black leather whip. Through what might have seemed to a casual viewer like a miracle of physics, the whip struck in precisely the right spot to send a single block flying from the stack while the rest of the tower remained structurally sound.