When we learn a new skill, the brain has to decide—cell by cell—what to change. New research from MIT suggests it can do that ...

Continual learning in neural networks addresses the challenge of adapting to new information accumulated over time while retaining previously acquired knowledge. A central obstacle to this process is ...

Researchers have unveiled a new generation of photonic computing chips capable of performing real‑time learning and decision‑making using only light-based processes. Photonic chips deliver real‑time ...

Researchers have developed photonic computing chips that overcome key limitations for a type of neural network known as a ...

Learn about the most prominent types of modern neural networks such as feedforward, recurrent, convolutional, and transformer networks, and their use cases in modern AI. Neural networks are the ...

Researchers have built new photonic computing chips that allow neural networks to learn using ...

MicroCloud Hologram Inc. (NASDAQ: HOLO), ("HOLO" or the "Company"), a technology service provider, released a core quantum machine learning technology oriented toward sequential learning tasks—the ...

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 ...

The TLE-PINN method integrates EPINN and deep learning models through a transfer learning framework, combining strong physical constraints and efficient computational capabilities to accurately ...

A two-chip photonic neuromorphic system performs real time spiking reinforcement learning using only light, achieving ...