Is Axiomatics Better Than Data Science?
The Case from Physics
In Brief: Euclid, the father of modern geometry, may be thought of as the father of logic itself. His axiomatization of geometry and embrace of rigor may be thought of as the beginning of the “formalist” school of A.I.
How does this compare to the current crop of “data sciencey” A.I.? Can these two divergent streams of A.I. (one much more in currency than the other, these days) converge? In this semi-philosophical talk, we will discuss logic, data science, physics and the relations between these. To illustrate the connections between these fields, we will use examples from continuum mechanics of solids and fluids.
Target Audience: This lecture is for computer scientists, physicists, engineers, mathematicians and statisticians. The first one hour is at a “popular science / philosophy” level, and could be enjoyed by everyone.
(Part 1: 1 hour) Logic; data science; physics; continuum mechanics; the philosophy of science.
Prerequisites: A general interest is enough to attend the first part. The second part will require some basic knowledge of linear algebra and calculus.
Teacher's Introduction: Udayan Kanade did his MS in Computer Science with the specialization “Optimization and Signal Processing” from Stanford. He works at Oneirix Labs and Noumenon Multiphysics.
Location: PLEASE NOTE. This lecture will be held in San Jose, California.