A new approach has been proposed to address the problem of "overconfidence"—one of the most critical risks of artificial ...

Spiking Neural Networks (SNNs) represent the "third generation" of neural models, capturing the discrete, asynchronous, and energy-efficient nature of ...

Neural networks are able to build personalized learning of a foreign language, eliminating the main psychological barrier — ...

The human brain begins learning through spontaneous random activities even before it receives sensory information from the external world. The technology developed by the KAIST research team enables ...

Previously met with skepticism, AI won scientists a Nobel Prize for Chemistry in 2024 after they used it to solve the protein folding and design problem, and it has now been adopted by biologists ...

Artificial intelligence systems based on neural networks—such as ChatGPT, Claude, DeepSeek or Gemini—are extraordinarily ...

Researchers use statistical physics and "toy models" to explain how neural networks avoid overfitting and stabilize learning in high-dimensional spaces.

Machine learning is a subfield of artificial intelligence, which explores how to computationally simulate (or surpass) humanlike intelligence. While some AI techniques (such as expert systems) use ...

As members of the inaugural graduating class in Ohio University’s artificial intelligence program, three students share what ...

More than a billion people are now using artificial intelligence (AI) models regularly, for purposes ranging from work to advice about personal relationships. This trend began with the introduction of ...