Explore serverless machine learning inference with KFServing in this conference talk. Learn how KFServing leverages KNative to simplify deployment of standard and custom ML models, enabling auto-scaling and scale-to-zero functionality. Discover the challenges of integrating serverless technology with ML inference, particularly in latency-critical environments. Gain insights into the evolution of inference stacks, GPU autoscaling challenges, and strategies to improve GPU utilization. Examine a real-world use case of personalized news monitoring and the proposed multi-model inference service solution. Delve into practical experiences of running a serverless inference platform, including techniques to reduce tail latency and cold start latency. Understand the importance of monitoring and alerting for control plane, access logs, and inference service metrics. Get a glimpse of the KFServing roadmap for 2020 and learn about the open working group driving its development.