Researchers have developed photonic computing chips that overcome key limitations for a type of neural network known as a photonic spiking neural system. By enabling fast learning and decision making ...

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

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 ...

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 ...

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 ...

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 generated images from noise, using orders of magnitude less energy than current generative AI models require.

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 ...

Machine learning enhances proteomics by optimizing peptide identification, structure prediction, and biomarker discovery.