Accelerating the Speed of AI

Means of speeding p AI, decreasing energy use.

Accelerating AI computing to the speed of light   by University of Washington  in TechxPlore

Artificial intelligence and machine learning are already an integral part of our everyday lives online. For example, search engines such as Google use intelligent ranking algorithms, and video streaming services such as Netflix use machine learning to personalize movie recommendations.

As the demands for AI online continue to grow, so does the need to speed up AI performance and find ways to reduce its energy consumption

Now a University of Washington-led team has come up with a system that could help: an optical computing core prototype that uses phase-change material. This system is fast, energy efficient and capable of accelerating the neural networks used in AI and machine learning. The technology is also scalable and directly applicable to cloud computing.

The team published these findings Jan. 4 in Nature Communications.

"The hardware we developed is optimized to run algorithms of an artificial neural network, which is really a backbone algorithm for AI and machine learning," said senior author Mo Li, a UW associate professor of both electrical and computer engineering and physics. "This research advance will make AI centers and cloud computing more energy efficient and run much faster."

 More information: Changming Wu et al, Programmable phase-change metasurfaces on waveguides for multimode photonic convolutional neural network, Nature Communications (2021). DOI: 10.1038/s41467-020-20365-z

Journal information: Nature Communications