Lighting the Way: The Revolutionary Shift to Optical AI Processors
University of Pittsburgh's Nathan Youngblood is pioneering optical computing to boost AI and computing efficiency, supported by significant grants and focused on creating a diverse tech workforce.
Shining a Light on New Solutions
Nathan Youngblood, an assistant professor at the University of Pittsburgh, has received grants from the NSF and AFOSR to advance his research in optical computing and phase-change materials. His work aims to develop more efficient and fast optical computing systems to overcome the limitations of current hardware. This research has the potential to enhance AI's computational power and improve the speed and efficiency of modern computing systems.
Improving Optical Computing
With the grants he has received, Youngblood will be exploring two different approaches to enhance the speed, reliability, and efficiency of optical computing. The first approach focuses on utilizing the wave-like nature of light to increase efficiency, while the second approach aims to improve optical memories to enhance computational throughput. Current optical processors are not powerful, accurate, or efficient enough to be fully utilized for AI, and Youngblood's research aims to address these limitations.
Addressing the Challenges of AI
Youngblood's CAREER Award focuses on developing high-efficiency optical computing hardware to address the challenges of artificial intelligence. As AI applications continue to grow, there is a need for computing power that can support them. Current computing methods generate unwanted heat when processing large amounts of data, while optical computing can process data much faster using light, without the heating issue. However, current optical processors are not powerful or efficient enough for AI. Youngblood's research aims to overcome these challenges.
Advancements in Modern Computing
Existing computer hardware has reached its limit, with data movement between memory and processing cores hindering computing speeds and creating heat. Through the Young Investigator Program, Youngblood will create photonic hardware that allows computation to occur in the optical memory array itself, reducing data movement. His research will improve the efficiency, reliability, and repeatability of electrically programmable phase-change photonic memory, design efficient photonic networks, and demonstrate a photonic in-memory accelerator. This work will contribute to the development of novel materials for optoelectronic computational systems.
