Smooth developer experience is fundamental in artificial intelligence designs. Development toolkits can streamline the preparation of trained neural networks for edge and low-latency data-center ...

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 ...

Many "AI experts" have sprung up in the machine learning space since the advent of ChatGPT and other advanced generative AI constructs late last year, but Dr. James McCaffrey of Microsoft Research is ...

The problem of hallucinations -- artificial intelligence (AI) models that assert falsehoods under a veneer of being authoritative -- has led some scholars to conclude that generative AI simply cannot ...

Researchers are training neural networks to make decisions more like humans would. This science of human decision-making is only just being applied to machine learning, but developing a neural network ...

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 ...

We’ve already seen the iconic 1993 video game Doom being played on devices ranging from a candy bar to a John Deere tractor to a Lego brick to E. Coli cells. Now, researchers at Google and Tel Aviv ...

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, ...