Technological Advancements in Photonics and Electronics: The Machine Learning Perspective
Authors :- S Tank, P Mishra, M Bandyopadhyay, JJ Rath
Publication :- Innovations and Dynamics in Photonics and Electronics, Springer, 2025
The intersection of machine learning, electronics, and photonics represents a significant technological breakthrough. By utilizing the characteristics of light, photonics provides remarkable speed and bandwidth for the processing and transfer of data. Electronics, when combined with developments in semiconductor technology, keep pushing the boundaries of computing hardware's performance and efficiency. Data analysis is revolutionized by machine learning, especially when neural networks are used because of their ability to recognize patterns and create prediction models. Applications include tailored medicine, autonomous systems, and image and speech recognition. Photonic integration with electronic systems allows for faster data transfer and lower latency, which improves neural network performance. With optical components, photonic neural networks can theoretically outperform conventional electronic processors in calculation speed. Innovations in artificial intelligence are accelerated by this integration, which supports the creation of machine learning models that are more effective. In this article, we discuss the latest advancements in the synergistic integration of machine learning and photonics, present current challenges, and explore opportunities for future research.