Since finishing grad school, I have been diving from physics into coding. It turns out that it probably is all the same thing at the end of the day! I came across a paper that discovered an exact mapping between the renormalization group, a central concept in modern physics, and deep learning, the latest and greatest machine learning algorithm. It’s crazy but makes sense. Both the physics idea and deep learning rely on looking at a system on a succession of different levels. This high level view of a system helps you to see the big picture. That is useful for self-driving cars and for finding phase transitions in condensed matter systems.

I am excited about the potential of machine learning and AI. It’s cool to think that my various seemingly different interests, could turn out to overlap in productive ways.

What if there are other hidden connections between totally different fields?