Deploying Machine Learning

Daniel discusses the complexities of deploying machine learning models in real-world scenarios, highlighting issues such as high costs, noisy training data, and vulnerabilities to adversarial attacks. He emphasizes the need for a deeper understanding of the differences between standard software deployment and machine learning, as well as ongoing research aimed at addressing these challenges.