The main problem with big tech's experiment with artificial intelligence (AI) is not that it could take over humanity. It's ...

We use this handy neural mechanism to learn, remember, solve problems and generally navigate our reality. “It’s a network effect,” said UC Santa Barbara mechanical engineering professor Francesco ...

Get Instant Summarized Text (Gist) A self-attention neural network model enables rapid and accurate prediction of radiation shielding designs for space reactors, achieving less than 3% deviation ...

Researchers combine acoustic monitoring with a neural network to identify fish activity on coral reefs by sound. They trained the network to sort through the deluge of acoustic data automatically ...

It's an AI-based upscaling solution that utilizes Recurrent Neural Networks (RNN), but to enable PSSR, Sony first had to create what it calls a "fully fused network." Okay, so let's go over what ...

Insights from the models reveal how connectivity shapes complex brain networks and how learning occurs through synaptic plasticity in realistic conditions. This work paves the way for studying ...

will today reveal several new AI models based on a novel type of “liquid” neural network that has the potential to be more efficient, less power-hungry, and more transparent than the ones that ...

Artificial neural networks are behind much of the AI technology we use today. In the same way your brain has neuronal cells linked by synapses, artificial neural networks have digital neurons ...

An April 2024 study introduced an alternative neural network design, called a Kolmogorov-Arnold network (KAN), that is more transparent yet can also do ... connect to each other using artificial ...

By integrating and connecting the developed devices, the team also successfully implemented the "neuron-synapse-neuron" structure, the basic unit block of an artificial neural network, in hardware ...