Flexible data centers can speed both AI scale and clean energy adoption | Ayse Coskun | TEDxBoston

Data centers have the earned their reputation as energy hogs. If we designed them to be more flexible, the demand load can be shaped to match the availability of clean power on the grid. Not all computing tasks are urgent. Batch jobs, model fine-tuning, and large-scale processing can wait minutes or hours without anyone noticing. If data centers can slow down when clean energy is scarce and speed up when renewables are abundant, they stop being the enemy of the grid and become one of its most useful tools. What began as whiteboard sketches rejected by funding agencies is now running on real-world data centers. Professor Ayse Coskun is the Chief Scientist at Emerald AI, a startup focused on enabling power flexibility in data centers. She is also a full professor in the Electrical and Computer Engineering Department at Boston University, where she leads the Center for Information and Systems Engineering and serves as Associate Dean for Research at the College of Engineering. Her research group is shaping the emerging field of flexible, grid-aware computing. More broadly, she applies AI and machine learning to optimize cloud and high-performance computing systems. She received the Ernest Kuh Award for energy-efficient system-level design and an IBM Faculty Award for applying AI-based methods in DevSecOps. Earlier in her career, Prof. Coskun worked in industry at Sun Microsystems (now Oracle). She currently serves as Deputy Editor-in-Chief of IEEE Transactions on Computer-Aided Design and holds a PhD in Computer Science and Engineering from the University of California, San Diego. ‍ This talk was given at a TEDx event using the TED conference format but independently organized by a local community. Learn more at https://www.ted.com/tedx