Scientists at La Jolla Institute for Immunology (LJI) are pioneering new methods in machine learning to better understand the inner workings of our cells. In a recent Genome Biology study, LJI ...

Artificial intelligence systems based on neural networks—such as ChatGPT, Claude, DeepSeek or Gemini—are extraordinarily ...

Neural networks have been powering breakthroughs in artificial intelligence, including the large language models that are now being used in a wide range of applications, from finance, to human ...

Ryan Clancy is an engineering and tech (mainly, but not limited to those fields!!) freelance writer and blogger, with 5+ years of mechanical engineering experience and 10+ years of writing experience.

Researchers use statistical physics and "toy models" to explain how neural networks avoid overfitting and stabilize learning in high-dimensional spaces.

In 2026, neural networks are achieving unprecedented efficiency, multimodal integration, and workflow comprehension, yet benchmarks like MLRegTest reveal persistent struggles with formal rule learning ...

Even networks long considered "untrainable" can learn effectively with a bit of a helping hand. Researchers at MIT's Computer Science and Artificial Intelligence Laboratory (CSAIL) have shown that a ...

A research team led by Associate Professor Hiroto Sekiguchi and graduate student Gota Shinohara from the Department of Electrical and Electronic Information Engineering at Toyohashi University of ...

A new study, published in Nature Communications this week, led by Jake Gavenas PhD, while he was a PhD student at the Brain Institute at Chapman University, and co-authored by two faculty members of ...

In the decades following the work by physiologist Ivan Pavlov and his famous salivating dogs, scientists have discovered how molecules and cells in the brain learn to associate two stimuli, like ...