Pavan discusses the balance between defining objects through physics and leveraging deep learning's data-driven approach. He emphasizes that while the exact amount of data needed remains uncertain, integrating physics-based constraints can enhance performance and stability in image processing tasks. This middle ground allows for a more efficient use of training data while still accommodating the complexities of deep learning.
