The Elephant in the Room: Fluid Dynamics in the age of Machine Learning
Prof. Matthew Juniper
Slide at 02:50
Summary (AI generated)
In the article from Nature that I read, it discussed the pseudoscalar mison theory. However, it was ultimately proven to be rubbish. The theory could only fit the data by adjusting arbitrary parameters, which were not meaningful or significant. Therefore, if we interpret this to mean that a physical model should have fewer than four parameters, we are doing ourselves a disservice. This was never the intention.
In fact, in today's era of abundant data, I believe that we can utilize physics-based models with more than four parameters. The main point of this talk is to assert that when we have a large amount of data, specifically millions of data points, we can effectively train models in physics that require more than just four parameters.