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 ...

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, ...

Implement Neural Network in Python from Scratch ! In this video, we will implement MultClass Classification with Softmax by making a Neural Network in Python from Scratch. We will not use any build in ...

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 AI-driven digital-predistortion (DPD) framework can help overcome the challenges of signal distortion and energy ...

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 ...

Physicists working with computer specialists have developed a so-called event-based architecture, using photonic processors. In a similar way to the brain, this makes possible the continuous ...

An MIT spinoff co-founded by robotics luminary Daniela Rus aims to build general-purpose AI systems powered by a relatively new type of AI model called a liquid neural network. The spinoff, aptly ...

The chip contains almost 8,400 functioning artificial neurons from waveguide-coupled phase-change material. The researchers trained this neural network to distinguish between German and English texts ...