- Feb. 8, 2023, 4:00 pm US/Central
- Nhan Tran, Fermilab
- Chris Stoughton
- Video
Pursuing answers to fundamental questions about our nature requires searches for the ultra-rare, very subtle, and the inspection of nature at extremely fine spatial and temporal scales. Cutting-edge experiments are often confronted with massive amounts of very rich data on which Artificial Intelligence (AI) techniques provide powerful insights. To accelerate scientific discovery, enabling powerful AI algorithms across the data processing continuum, as close to sensor front-ends as possible, is becoming increasingly valuable. To deploy AI in these challenging scientific environments, we require robust and efficient learning and usable and accessible tool flows for optimized training and implementation across a broad range of scientific domains. This talk will introduce the motivations and requirements for real-time AI applications for physics and connections to broader science and industry applications, the development of modern techniques for deploying them into our experiments, and open research questions and challenges.