May, L., et al. (2025). Pre-training artificial neural networks with spontaneous retinal activity improves motion prediction in natural scenes. PLoS Computational Biology.

Neural networks are a subset of machine learning, which is a technique used to help computers learn using training that is modeled on results gleaned from large data sets. As such, neural networks ...

As a result, researchers are increasingly turning to synthetic data to supplement or even replace natural data for training neural networks. “Machine learning has long been struggling with the data ...

A team from MIT's Computer Science and Artificial Intelligence Lab (CSAIL) says that understanding these representations, as well as how they inform the ways that neural networks learn from data ...

Deep neural networks are at the heart of artificial intelligence, ranging from pattern recognition to large language and ...

Artificial Neural Network Architecture. Scientists design ANNs to function like neurons. 6 They write lines of code in an algorithm such that there are nodes that each contain a mathematical function, ...

We’re told neural networks ‘learn’ the way humans do. A neuroscientist explains why that’s not the case — and why AI can't think like us yet.

Artificial neural networks learn better when they spend time not learning at all. ScienceDaily . Retrieved June 2, 2025 from www.sciencedaily.com / releases / 2022 / 11 / 221118160305.htm ...

Engineers have uncovered an unexpected pattern in how neural networks -- the systems leading today's AI revolution -- learn, suggesting an answer to one of the most important unanswered questions ...

Artificial neural networks learn better when they spend time not learning at all UC San Diego researchers found that periods off-line during training mitigated “catastrophic forgetting” in ...

For decades, scientists have looked to light as a way to speed up computing. Photonic neural networks—systems that use light ...