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.

In 2026, neural networks are achieving unprecedented efficiency, multimodal integration, and workflow comprehension, yet benchmarks like MLRegTest reveal persistent struggles with formal rule learning ...

During my first semester as a computer science graduate student at Princeton, I took COS 402: Artificial Intelligence. Toward the end of the semester, there was a lecture about neural networks. This ...

A study using the MLRegTest benchmark tested 1,800 artificial languages to evaluate whether neural networks can learn underlying rules rather than just patterns. The results show that while models ...

Neural networks power today’s AI boom. To understand them, all we need is a map, a cat and a few thousand dimensions. Look at a picture of a cat, and you’ll instantly recognize it as a cat. But try to ...

ChatGPT has triggered an onslaught of artificial intelligence hype. The arrival of OpenAI’s large-language-model-powered (LLM-powered) chatbot forced leading tech companies to follow suit with similar ...

It has been unclear how to build simulations of entire neural circuits with only measurements from a dead fly’s brain. Using machine learning to combine a wiring diagram with knowledge of the ...