AI became powerful because of interacting mechanisms: neural networks, backpropagation and reinforcement learning, attention, training on databases, and special computer chips.

Artificial intelligence systems designed to physically emulate natural brains can simulate human brain activity before being trained, according to new research from Johns Hopkins University. “The work ...

SHANNON, CLARE, IRELAND, February 5, 2026 /EINPresswire.com/ -- A new publication from Opto-Electronic Technology; DOI ...

Blending logic systems with the neural networks that power large language models is one of the hottest trends in artificial intelligence. Now, however, the computer-science community is pushing hard ...

OpenAI researchers are experimenting with a new approach to designing neural networks, with the aim of making AI models easier to understand, debug, and govern. Sparse models can provide enterprises ...

Forbes contributors publish independent expert analyses and insights. Dr. Lance B. Eliot is a world-renowned AI scientist and consultant. In today’s column, I examine some exciting research that could ...

Yann LeCun is a leading AI voice whose pathbreaking work in neural networks became the foundation for modern computers and deep learning.

Talking to yourself feels deeply human. Inner speech helps you plan, reflect, and solve problems without saying a word.

A team at the University of California, San Diego has redesigned how RRAM operates in an effort to accelerate the execution ...

Google's Genie generates infinite interactive worlds from text. The secret? AI models compress reality's rules into transferable principles, enabling boundless creation.