Embracing Complexity

Rich Sutton advocates for embracing complexity in machine learning, urging researchers to move away from building models by hand and towards using lots of compute power. The discussion delves into the concept of neats and scruffies, highlighting the divide between those who focus on logic systems and those who prioritize real-world problem-solving and human data in ML research.