Stanford researchers have developed an innovative computer vision model that recognizes the real-world functions of objects, ...

Labeling images is a costly and slow process in many computer vision projects. It often introduces bias and reduces the ability to scale large datasets. Therefore, researchers have been looking for ...

A survey of reasoning behaviour in medical large language models uncovers emerging trends, highlights open challenges, and introduces theoretical frameworks that enhance reasoning behaviour ...

Artificial intelligence (AI) systems can be fooled by certain image inputs. Called adversarial examples, they incorporate ...

In 2008, Pietro Perona , Caltech's Allen E. Puckett Professor of Electrical Engineering, was on sabbatical in Italy, enjoying a cappuccino in a ...

Say a person takes their French Bulldog, Bowser, to the dog park. Identifying Bowser as he plays among the other canines is ...

For a long time, the core idea in reinforcement learning (RL) was that AI agents should learn every new task from scratch, like a blank slate. This "tabula rasa" approach led to amazing achievements, ...

Data originates at the edge, and processing it locally unlocks powerful real-time efficiencies that open very rich product ...

The new framework solves AI's "data bottleneck" by automatically generating high-quality training examples from raw screen ...

Haozhe "Harry" Wang's electrical and computer engineering lab at Duke welcomed an unusual new lab member this fall: ...

MBZUAI, UAE’s AI-only university, builds talent and open models for underserved languages, linking research, industry and policy for human-AI solutions to global problems ...

The availability of advanced sensors, artificial intelligence, digital twins, XR and robotics has changed technology-driven markets. We see how the intersection of these mutualistic technologies will ...