Perceptual decision-making involves distributed networks spanning both association cortices and subcortical areas. A fundamental question is whether such a network is highly redundant, or each node is ...

Humans constantly solve different instances of similar problems. We brake at stop signs, stop at red lights and slow down in crowded streets. We do these things effortlessly and efficiently learn to ...

Assistant Professor of Electrical and Computer Engineering Jason Eshraghian. Four years ago, UC Santa Cruz’s Jason Eshraghian developed a Python library that combines neuroscience with artificial ...

An open source code library for brain-inspired deep learning, called 'snnTorch,' has surpassed 100,000 downloads and is used in a wide variety of projects. A new paper details the code and offers a ...

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 ...

“Neural networks are currently the most powerful tools in artificial intelligence,” said Sebastian Wetzel, a researcher at the Perimeter Institute for Theoretical Physics. “When we scale them up to ...

AI thrives on data but feeding it the right data is harder than it seems. As enterprises scale their AI initiatives, they face the challenge of managing diverse data pipelines, ensuring proximity to ...

ChatGPT has triggered an onslaught of artificial intelligence hype. The arrival of OpenAI’s large-language-model-powered (LLM-powered) chatbot forced leading tech companies to follow suit with similar ...

The brain is the perfect place to look for inspiration to develop more efficient neural networks. Spiking neural networks are pervading many streams of deep learning which are in need of low-power, ...