Biology-inspired, silicon-based computing may boost AI efficiency; AMP2 instead uses AI to accelerate anaerobic biology.

AI methods are increasingly being used to improve grid reliability. Physics-informed neural networks are highlighted as a ...

The paper addresses the AI shutdown problem, a long-standing challenge in AI safety. The shutdown problem asks how to design AI systems that will shut down when instructed, will not try to prevent ...

At the heart of the friction is a simple contrast. The ledger must be immutable, reconcilable to the last decimal, and ...

Artificial intelligence is colliding with a hard physical limit: the energy and heat of conventional chips. As models scale ...

Are we seeing a stall in the EVolution while the rate of AI acceleration continues to quicken?” This is what permeates all of the events that have taken place within a week when Ford pulled its ...

A research team from the Xinjiang Astronomical Observatory (XAO) of the Chinese Academy of Sciences has developed an interpretable artificial intelligence (AI) framework named Convolutional Kolmogorov ...

AI has successfully been applied in many areas of science, advancing technologies like weather prediction and protein folding ...

Neural and computational evidence reveals that real-world size is a temporally late, semantically grounded, and hierarchically stable dimension of object representation in both human brains and ...

Neuroscience continually strives to unravel the intricate relationship between neural network morphology, spiking dynamics, and their resulting functional ...

Wolfram-like attention framing meets spiking networks: event-triggered, energy-thrifty AI that “wakes” to stimuli.