Silicon Photonics

Silicon photonics leverages the unique properties of light to create highly efficient and parallel computing architectures, aiming to overcome limitations of traditional electronic systems. Current research focuses on developing photonic hardware accelerators for various machine learning models, including transformers, recurrent neural networks, and graph neural networks, often employing reservoir computing and direct feedback alignment training algorithms. This approach promises significant improvements in throughput and energy efficiency for applications ranging from large language models to image processing and graph analysis, potentially revolutionizing artificial intelligence and high-performance computing.