That data could be the fuel for machine learning and other kinds of computation that could help us make develop drugs faster and make smarter decisions about care. In fields from drug development to frontline medical care, we’ve got petabytes of data to work with, in the form of electronic medical records, genomic and proteomic data, and clinical trial data. Longtime listeners know that data interoperability in healthcare, or more often the lack of interoperability, is a repeating theme of the show. Together with two former MIT mathematicians, Daimler co-founded a company called Conexus that uses category theory to tackle the problem of data interoperability. It can be used to prove that different structures are consistent or compatible with one another, and to prove that the relationships in a dataset are still intact even after the data has been transformed in some way.
An increasingly important in computer science, category theory is about the relationships between sets or structures. Instead he says you should study category theory. If you’re a young person today trying to decide which math course you’re going to take-or maybe an old person who just wants to brush up-he says you shouldn’t bother with trigonometry or calculus.
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Harry's guest Eric Daimler, a serial software entrepreneur and a former Presidential Innovation Fellow in the Obama Administration, has an interesting argument about math.
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