Optical Computing

Optical computing harnesses the speed and parallelism of light to accelerate computation, primarily focusing on addressing the limitations of electronic computing in handling the massive datasets and complex algorithms of modern artificial intelligence. Current research emphasizes the development of optical neural networks, employing architectures like convolutional neural networks and transformers, and exploring novel training methods such as model-free optimization and processing-in-memory techniques to improve efficiency and accuracy. This field holds significant promise for enhancing the speed and energy efficiency of AI applications, particularly in areas like image processing, machine learning, and high-speed data communication.