Machine Learning Challenges

Kyle and Damian discuss the challenges of deploying machine learning models, highlighting the difficulty in detecting performance issues compared to traditional software releases. They emphasize the importance of continuous monitoring and hypothesis-driven development in evaluating model effectiveness over time.