Researchers at the University of Texas have discovered a new way for neural networks to simulate symbolic reasoning. This discovery sparks an exciting path toward uniting deep learning and symbolic ...

Neural networks are computing systems designed to mimic both the structure and function of the human brain. Caltech researchers have been developing a neural network made out of strands of DNA instead ...

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.

A hands-on guide to building and training a two-hidden-layer neural network regressor in C#, including data preparation, SGD, evaluation, and using the trained model.

“Foundation models are deep neural networks (such as GPT-5, Gemini~3, and Opus~4) trained on large datasets that can perform diverse downstream tasks — text and code generation, question answering, ...

This research shows that photonic neural networks don't need to follow the same rules as digital ones. By using the physical properties of light directly—rather than trying to simulate them—scientists ...

When trying to solve problems, artificial intelligence often uses neural networks to process data and make decisions in a way that mimics the human brain. In his latest research, Binghamton University ...