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Using geometry and physics to explain feature learning in deep neural networks

Deep neural networks (DNNs), the machine learning algorithms underpinning the functioning of large language models (LLMs) and other artificial intelligence (AI) models, learn to make accurate ...
Frontiers

NeuroAI and the brain: Integrating brain-inspired computational models and large-scale AI architectures with computational theories of neural function

The rapid ascent of large-scale artificial intelligence has provided neuroscience with a new set of powerful tools for modeling complex cognitive functions.
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AI Researchers Are Confronting Rule Generalization Limits Revealed by MLRegTest

In 2026, neural network research is advancing in efficiency, adaptability, and workflow reasoning, yet the MLRegTest benchmark shows persistent weaknesses in rule generalization. Researchers are ...
Wall Street Journal

Meet Neurosymbolic AI, Amazon’s Method for Enhancing Neural Networks

Neural networks aren’t the only game in artificial intelligence, but you’d be forgiven for thinking otherwise after the hot streak sparked by ChatGPT’s arrival in 2022. That model’s abilities, ...
Ars Technica

Researchers isolate memorization from problem-solving in AI neural networks

When engineers build AI language models like GPT-5 from training data, at least two major processing features emerge: memorization (reciting exact text they’ve seen before, like famous quotes or ...