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

Smarter study help: LLM-powered tutors like Physics-STAR offer step-by-step guidance that boosts efficiency and understanding, especially for complex physics problems. Beyond the classroom: AI tools ...

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

Harvard University physicists have developed a simplified, physics-inspired mathematical model to better understand how neural networks learn. Published in the Journal of Statistical Mechanics, the ...

AI excels at correlations but lacks physical intuition, creating gaps in real-world reasoning and reliability.

Now, artificial intelligence (AI) tools are providing powerful new ways to address long-standing problems in physics. “The ...

Researchers present a comprehensive review of frontier AI applications in computational structural analysis from 2020 to 2025, focusing on graph neural networks (GNNs), sequence-to-sequence (Seq2Seq) ...

IN 2025 A GROUP of theoretical physicists studying the behaviour of fundamental particles called gluons hit a brick wall in their calculations. In search of a fresh perspective, the physicists teamed ...

Dyad AI from JuliaHub is bringing an AI-for-Science environment to product development. Users can model and interrogate systems, research formulations, derive governing equations, assemble models, run ...

Generative AI is becoming ubiquitous in everyday life. Large language models like ChatGPT can help answer questions, write email, and solve problems at seemingly lightning speed, pulling from enormous ...