Ten years after a milestone victory, AI now dominates Go training. Players are figuring out what that means for the game.

Data is the life-blood of physical AI. Collecting real-life data is expensive. Generative AI and diffusion to create ...

A new study reveals that the next generation of blockchain defenses will not rely on fixed rules alone but on adaptive, learning-based systems capable of evolving alongside intelligent adversaries.

In a small lab at the University of California, Santa Cruz, clusters of mouse brain cells have taken on a task normally reserved for computer algorithms: ...

Researchers generated images from noise, using orders of magnitude less energy than current generative AI models require.

A team of EPFL researchers has developed an AI algorithm that can model complex dynamical processes while taking into account ...

Researchers at the University of California, Santa Cruz have trained lab-grown brain organoids to solve a goal-directed task, ...

UC Santa Cruz researchers are exploring how brains learn, adapt, and improve, which could help us better understand and address neurological conditions.

Accurately tracking atmospheric greenhouse gases requires not only fast predictions but also reliable estimates of ...

This AI system identifies clinically significant valvular heart disease from stethoscope recordings, achieving near-clinical ...

AI became powerful because of interacting mechanisms: neural networks, backpropagation and reinforcement learning, attention, training on databases, and special computer chips.

Massive computing systems are required to train neural networks. The prodigious amount of consumed energy makes the creation of AI applications significant polluters ...