New research from the University of St Andrews, the University of Copenhagen and Drexel University has developed AI ...

The application of neural network models to semiconductor device simulation has emerged as a transformative approach in the field of electronics. These models offer significant speed improvements over ...

Listen to the first notes of an old, beloved song. Can you name that tune? If you can, congratulations — it’s a triumph of your associative memory, in which one piece of information (the first few ...

When engineers build AI language models like GPT-5 from training data, at least two major processing features emerge: memorization (reciting exact text they’ve seen before, like famous quotes or ...

Calculations show that injecting randomness into a quantum neural network could help it determine properties of quantum ...

Nvidia’s latest pitch for the future of graphics is not about more polygons or higher memory bandwidth, it is about teaching ...

A Performant Side-channel-Resistant RISC-V Core Securing Edge AI Inference” was published by researchers at Northeastern ...

Machine learning and neural nets can be pretty handy, and people continue to push the envelope of what they can do both in high end server farms as well as slower systems. At the extreme end of the ...

The representation of individual memories in a recurrent neural network can be efficiently differentiated using chaotic recurrent dynamics.

Researchers have employed Bayesian neural network approaches to evaluate the distributions of independent and cumulative ...

Facial expression control starts in a very old part of the nervous system. In the brain stem sits the facial nucleus, which ...