A team at Carnegie Mellon University is helping kids understand artificial intelligence with a soft, squishy, LED-lit neural ...

This blog post is the second in our Neural Super Sampling (NSS) series. The post explores why we introduced NSS and explains its architecture, training, and inference components. In August 2025, we ...

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.

Machine learning is now living through a justified hype as organizations uncover more and more of its potential benefits. The algorithms produce accurate results and hence provide real value to ...

Using single-cell RNA sequencing and genetic screening, the researchers identified key surface proteins that mediate ...

A new book by one of the founders of research on neural networks covers more than 40 years of scientific work that led to the ...

Unlike their more modern large language model counterparts, artificial neural networks require human input to learn and function. ANNs have been around since the 1950s. They started taking hold in ...

For the past decade, AI researcher Chris Olah has been obsessed with artificial neural networks. One question in particular engaged him, and has been the center of his work, first at Google Brain, ...

The curious minds at ColdFusion explain how neural networks are transforming on-the-go computing. This matters because ...

In 1943, a pair of neuroscientists were trying to describe how the human nervous system works when they accidentally laid the foundation for artificial intelligence. In their mathematical framework ...

Our brains actively construct vision in near-darkness, blending residual light with memory and prediction. Even with minimal ...

Florida Atlantic University neuroscientists have uncovered a surprising role for a protein named "Frazzled" (known as DCC in ...