Is AI what's for Fluids Next?

The Nobel prize for chemistry awarded to the AlphaFold team and efforts to create AI scientists (Autoscience Institute) seem to indicate a clear path for the future of science. Today LRMs (large reasoning models) can easily pass exams in undergraduate and graduate fluids classes, but it is unclear if or how this objective competence translates into insight, knowledge and ultimately discovery. I will start with a historical perspective on the role of inductive and deductive thinking in science and assess where current LRM models appear to be. Then I will focus on how AI can accelerate the “classic" scientific process (observation-inquiry-hypothesis-experiment-analysis) and discuss some of the current critical bottlenecks. The main focus will be on how the study of turbulence has evolved and is now impacted by AI. I will also provide a perspective on the status and adoption of AI in engineering applications of fluid dynamics.