Adaptive method helps light-based quantum processors act more like neural networks

Machine learning models called convolutional neural networks (CNNs) power technologies like image recognition and language ...
Tech Xplore on MSN

A brain-like chip interprets neural network connectivity in real time

The ability to analyze the brain's neural connectivity is emerging as a key foundation for brain-computer interface (BCI) ...

Hybrid Quantum: Classical Architectures For Machine Learning

As you begin your hybrid quantum approach, here are the advantages, use cases and limitations to keep in mind.
optics.org

Rome-led group progresses toward practical photonic quantum neural networks

Photons are fast, stable, and easy to manipulate on chips, making photonic systems a promising platform for QCNNs. However, ...
Semiconductor Engineering

Deep Learning Neural Networks Drive Demands On Memory Bandwidth

A deep neural network (DNN) is a system that is designed similar to our current understanding of biological neural networks in the brain. DNNs are finding use in many applications, advancing at a fast ...

Interpretable machine learning to accelerate nanocatalyst discovery

A fast and accurate surrogate model screens over 10,000 possible metal-oxide supports for a platinum nanocatalyst to prevent sintering under high temperatures.
Lifehacker

What Neural Networks, Artificial Intelligence, and Machine Learning Actually Do

When an app claims to be powered by “artificial intelligence” it feels like you’re in the future. What does that really mean, though? We’re taking a look at what buzzwords like AI, machine learning, ...

Transformer AI models outperform neural networks in stock market prediction, study shows

Like other sectors of society, artificial intelligence is fundamentally changing how investors, traders and companies make ...