Chris shares his experience in self-driving technology, emphasizing the importance of structured testing for deep learning systems. He highlights the need for practical evaluation methods as models and datasets scale, leading to improved completion rates. Daniel probes into the evolution of generative models, hinting at the lessons learned from past iterations that inform current approaches.
