As an emerging technology in the field of artificial intelligence (AI), graph neural networks (GNNs) are deep learning models designed to process graph-structured data. Currently, GNNs are effective ...

A team at the University of California, San Diego has redesigned how RRAM operates in an effort to accelerate the execution ...

Neural network models that are able to make decisions or store memories have long captured scientists' imaginations. In these models, a hallmark of the computation being performed by the network is ...

An AI-driven digital-predistortion (DPD) framework can help overcome the challenges of signal distortion and energy inefficiency in power amplifiers for next-generation wireless communication.

Robot perception and cognition often rely on the integration of information from multiple sensory modalities, such as vision, ...

Lightweight convolutional neural networks improved lung cancer classification accuracy in histopathological images while ...

Human memory and attention are core cognitive functions that shape perception, learning, and decision-making. And whilst decades of research have provided ...

A hunk of material bustles with electrons, one tickling another as they bop around. Quantifying how one particle jostles others in that scrum is so complicated that, beginning in the 1990s, physicists ...

Multiverse’s flagship product is a platform called CompactifAI that reduces the amount of infrastructure needed to run AI models. According to the company, the software can halve training times and ...