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

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

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 ...

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 ...

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

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 ...

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.

Researchers develop TweetyBERT, an AI model that automatically decodes canary songs to help neuroscientists understand the neural basis of speech.