Explore a conference talk on Ekya, a system for continuous learning of video analytics models on edge compute servers. Dive into the challenges of balancing inference and retraining tasks, addressing data drift, and optimizing resource allocation. Learn how Ekya outperforms baseline schedulers, achieving 29% higher accuracy gain and requiring 4x fewer GPU resources. Discover the intricacies of edge video analytics, the cost of continuous learning, and innovative scheduling decisions. Gain insights into Ekya's design, including its Thief Scheduler, and understand its performance in scaling with increasing video streams.