Julia

In programming language circles there’s a recently trend of discussing a concept called zero-cost abstractions: the ability to use higher-levels abstractions without suffering any loss of performance. Zero-cost abstractions allows you to write performant code without having to give up a single drop of convenience and expressiveness: You want for-loops? You can have it. Generics? Yeah, why not? Data structures? Sure, keep’em coming. Async operations? You bet ya! Multi-threading? Hell yes! ...

Warning: This post has KaTeX enabled, so if you want to view the rendered math formulas, you’ll have to unfortunately enable JavaScript. Dennis Lindley, one of my many heroes, was an English statistician, decision theorist and leading advocate of Bayesian statistics. He published a pivotal book, Understanding Uncertainty, that changed my view on what is and how to handle uncertainty in a coherent1 way. He is responsible for one of my favorites quotes: “Inside every non-Bayesian there is a Bayesian struggling to get out”; and one of my favorite heuristics around prior probabilities: Cromwell’s Rule2. Lindley predicted in 1975 that “Bayesian methods will indeed become pervasive, enabled by the development of powerful computing facilities” (Lindley, 1975). You can find more about all of Lindley’s achievements in his obituary. ...

Warning: This post has KaTeX enabled, so if you want to view the rendered math formulas, you’ll have to unfortunately enable JavaScript. I wish I could go back in time and tell my younger self that you can make a machine understand human language with trigonometry. That would definitely have made me more aware and interested in the subject during my school years. I would have looked at triangles, circles, sines, cosines, and tangents in a whole different way. Alas, better late than never. ...