It now appears that neural nets may be the next frontier in the advance of computing technology as a whole. But what are ...

Networks programmed directly into computer chip hardware can identify images faster, and use much less energy, than the traditional neural networks that underpin most modern AI systems.

An innovative planar spoof plasmonic neural network (SPNN) platform capable of directly detecting and processing terahertz (THz) electromagnetic signals has been unveiled by researchers at City ...

The initial research papers date back to 2018, but for most, the notion of liquid networks (or liquid neural networks) is a new one. It was “Liquid Time-constant Networks,” published at the ...

Learn More In the current artificial intelligence (AI) landscape, the buzz around large language models (LLMs) has led to a race toward creating increasingly larger neural networks. However ...

Machine learning with neural networks is sometimes said to be part art and part science. Dr. James McCaffrey of Microsoft Research teaches both with a full-code, step-by-step tutorial. A binary ...

Using liquid neural networks, researchers at the Massachusetts Institute of Technology have trained a drone to identify and navigate toward objects in varying environments. Liquid neural networks ...

Dr. James McCaffrey of Microsoft Research says a neural network model is arguably the most powerful multi-class classification technique. A multi-class classification problem is one where the goal is ...

Learn More Artificial intelligence (AI) has made tremendous progress since its inception, and neural networks are usually part of that advancement. Neural networks that apply weights to variables ...

As it happens, that’s what scientists have just done with mathematics. Researchers have examined a deep neural network—one type of artificial intelligence, a type that’s notoriously ...

Modeled on the human brain, neural networks are one of the most common styles of machine learning. Get started with the basic design and concepts of artificial neural networks. Artificial ...

My colleagues and I based our new material’s architecture on that of an artificial neural network – layers of interconnected nodes that can learn to do tasks by changing how much importance ...