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 ...
Frontiers

Robotics & machine learning for understanding neural networks

Biological neural networks are immensely complex systems underlying all aspects of cognition and behavior. Despite significant advances in neuroscience, a ...
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) ...
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 ...

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, ...
Quanta Magazine

A New Link to an Old Model Could Crack the Mystery of Deep Learning

In the machine learning world, the sizes of artificial neural networks — and their outsize successes — are creating conceptual conundrums. When a network named AlexNet won an annual image recognition ...

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 ...