About cookies on this site Our websites require some cookies to function properly (required). In addition, other cookies may be used with your consent to analyze site usage, improve the user experience and for advertising. For more information, please review your options. By visiting our website, you agree to our processing of information as described in IBM’sprivacy statement. To provide a smooth navigation, your cookie preferences will be shared across the IBM web domains listed here.
Publication
CLEO/Europe-EQEC 2023
Conference paper
Motivation and challenges for applying photonic neuromorphic computing technologies
Abstract
Artificial intelligence is playing an increasingly important role. The recent announcement of ChatGPT [1] and the following discussion on its economic impact is clearly demonstrating this. ChatGPT is based on the GPT-3 neural network; an architecture with over 100 billion parameters. The training and execution of networks with so many parameters are taking a large amount of energy [2], it is hence of utmost importance to explore new concepts and hardware that can make the important operations in neural networks more power efficient.