We may be closer to understanding how AI models think, giving researchers new tools to ensure they don't go rogue.

Researchers have developed an attention-enhanced residual network that converts structural vibration data into Markov ...

As artificial intelligence becomes more powerful, its ability to handle humanlike tasks is undeniable. Artificial neural ...

A three-year project led by Joshua Burby will build neural network models to explore new stellarator designs and lower the ...

When humans write sentences or solve math problems, they are thinking symbolically—each number, variable or word is expressed ...

Goodfire researcher Nick Cammarata argues nearly 90% of neurons in models like Qwen3-32B have one clear role, up from about 2 ...

Hello, this is Yakumo.What is AI in the first place?The AI Basics Course, which started from that very question, has ...

The writer Malcolm Gladwell popularized the term "tipping points" to refer to the moment when a trend or social behavior ...

Neuro-symbolic AI combines neural networks with rules-based symbolic processing techniques to improve artificial intelligence systems' accuracy, explainability and precision. The neural aspect ...

A neural network is a machine learning (ML) model designed to process data in a way that mimics the function and structure of the human brain. Neural networks are intricate networks of interconnected ...

A new graph neural network framework evaluates dance training in real time and automatically adapts practice plans, achieving ...

New research from the University of St Andrews, the University of Copenhagen and Drexel University has developed AI computational models that predict the degeneration of neural networks in amyotrophic ...