Accelerating Dark Matter discovery with Intelligent Detectors

The coming generation of experiments at high-intensity particle accelerators will provide new and powerful tools in the search for particle dark matter.  Detectors with extreme dynamic range and spatial segmentation will probe physical interactions at an unprecedented level of detail, maximizing our potential for discovery.  To fully capitalize on these intense beams and highly-precise detectors, searches must face the formidable challenge of processing extreme data rates to efficiently identify subtle signatures of New Physics amongst an overwhelming background.  I will discuss how recent developments in real-time machine learning have led toward promising solutions to these challenges, drawing on examples from CMS, the Light Dark Matter eXperiment (LDMX), and beyond.