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 ...
TMCnet

WiMi Studies Hybrid Quantum-Classical Learning Architecture for Multi-Class Image Classification

In this architecture, the training process adopts a joint optimization mechanism based on classical cross-entropy loss. WiMi treats the measurement probability distribution output by the quantum ...

How Does AI Work? Understanding the Basics of Artificial intelligence

If you are curious and want to learn how does AI work, well, follow our detailed explainer on Artificial Intelligence's ...
Tech Xplore on MSN

Overparameterized neural networks: Feature learning precedes overfitting, research finds

Modern neural networks, with billions of parameters, are so overparameterized that they can "overfit" even random, ...
Tyler Morning Telegraph

Neural networks, machine learning? Nobel-winning AI science explained

The Nobel Prize in Physics was awarded to two scientists on Tuesday for discoveries that laid the groundwork for the artificial intelligence used by hugely popular tools such as ChatGPT.
eWeek

Neural Networks vs. Deep Learning

Binary digits and circuit patterns forming a silhouette of a head. Neural networks and deep learning are closely related artificial intelligence technologies. While they are often used in tandem, ...
Electronic Design

Neuromorphic NPU Sips Power to Handle Edge Machine-Learning Models

What are spiking neural networks (SNNs)? Why the Akida Pico neural processing unit (NPU) can use so little power to handle machine-learning models. Why neuromorphic computing is important to ...