From forgotten neural networks to the deep learning boom and the shift from predictive to generative AI – here’s how machine ...

Deep neural networks are at the heart of artificial intelligence, ranging from pattern recognition to large language and ...

Four of the 25 most-cited scientific papers of the 21st century were authored or co-authored by University of Toronto ...

Conventional robots, like those used in industry and hazardous environments, are easy to model and control, but are too rigid ...

International annual awards program honors standout AI companies and solutions ...

A I is everywhere. From the massive popularity of ChatGPT to Google cramming AI summaries at the top of its search results, ...

Despite the recent announcement from the Department of Defense (DoD), I posit that Artificial Intelligence (AI) cannot ...

The study’s authors note that small neural networks — simplified versions of the neural networks typically used in commercial ...

The conventional approach to learning to play games involves training neural networks through what is known as deep reinforcement learning, which involves experimenting and tweaking their ...

MicroCloud Hologram Inc. announces a noise-resistant Deep Quantum Neural Network architecture, advancing quantum computing and machine learning efficiency.

These schemes integrate Deep Reinforcement Learning (DRL) and Graph Neural Networks (GNNs) to construct efficient tree topologies with the goal of maximizing the minimum throughput of the wireless ...

Deep learning A subset of self-improving machine learning in which AI algorithms are designed with a multi-layered, artificial neural network (ANN) structure.