Author is talking about how our physical theories, such as QFT, currently have more predictive power than any theories we currently have about machine learning/deep learning.
(Author has a PhD in theoretical physics).
In practice, the computations required to use the QFT model are just too complex for modern computers when it comes to single atoms with more than a few protons, not to mention larger molecules. Instead, we must use simplified models like the Bohr model to make predictions about molecular bonds.
This actually seems to be very similar to AI where we understand not everything, but a lot about basic neurons, yet the emergent phenomena of intelligence is very difficult to predict due to the explosion of computational complexity.
You will notice the article conflates the two things: physics and the known laws of physics (e.g. first para in section 1.2). Simplicity of the latter does not imply simplicity of the former, but the article assumes that it does in order to tackle/state the question as posed: "Why is AI hard and physics simple?".