Modern neural networks, with billions of parameters, are so overparameterized that they can "overfit" even random, ...

The Defense Advanced Research Projects Agency awarded Professor Jie Gu and co-PIs from the University of Minnesota and Duke University up to $3.8 million through the Scalable Analog Neural-networks ...

The award further highlights the growing parallels and interconnectedness between psychics and computer science. Neural networks, which draw inspiration from how the human brain uses neurons to take ...

Dr. Jongkil Park and his team of the Semiconductor Technology Research Center at the Korea Institute of Science and Technology (KIST) have presented a new approach that mimics the brain's learning ...

I was reading my psychology book the other day and it mentioned how people, in an attempt at programming computers that *think* like humans, created neural network programming- which is the closest ...

Prominent artificial intelligence research lab OpenAI LLC today released Triton, a specialized programming language that it says will enable developers to create high-speed machine learning algorithms ...

Photons are fast, stable, and easy to manipulate on chips, making photonic systems a promising platform for QCNNs. However, photonic circuits typically behave linearly, limiting the flexible ...

Learn about the most prominent types of modern neural networks such as feedforward, recurrent, convolutional, and transformer networks, and their use cases in modern AI. Neural networks are the ...