The simplified approach makes it easier to see how neural networks produce the outputs they do. A tweak to the way artificial neurons work in neural networks could make AIs easier to decipher.

Somdip is the Chief Scientist of Nosh Technologies, an MIT Innovator Under 35 and a Professor of Practice (AI/ML) at the Woxsen University. This may sound like science fiction, but the convergence of ...

Harvard physicists have developed a simplified mathematical model to better understand how neural networks learn, likening the work to Kepler’s early laws of planetary motion. The model could help ...

In 2026, neural networks are achieving unprecedented capabilities in workflow reasoning and cross-domain integration, yet benchmarks like MLRegTest expose persistent failures in rule abstraction and ...

“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 ...

Sometimes in the rush to explore our interactions with neural nets (often in the form of LLMs) we forget to think about our own operating system and how it works. Of course, scientists did spend a lot ...