I'd argue that there are essentially two problems in computer science: 1. Math. 2. Dealing with the hardware. Virtually all the ugliness is a product of the

I'd argue that there are essentially two problems in computer science: 1. Math. 2. Dealing with the hardware. Virtually all the ugliness is a product of the interface between these two areas. Dealing with the hardware requires a fascination with minutiae and imperfection, while working in Math requires a fascination with generalities and perfection. The people on the math side create systems like Haskell, which let you express very abstract concepts, and reason very generally about your code, but make dealing with hardware issues difficult. The people on the hardware side use things like Forth, which is very powerful for building code that works closely with the hardware, but whose paradigms actively discourage the generality present in many other languages. And so, what's needed is someone who can develop a system that can fully express high level math concepts in such a way that there is a straightforward mapping to the messy world of hardware capabilities. However, I think the "killing blow" for pure programmers' motivations comes when they realize that mapping between the pure world of math and the messy world of hardware isn't enough. The focus on "end users" is the tacit admission that even if you do successfully build a beautiful system, most people don't want to work at a high level of mathematical abstraction. If you really want to revolutionize computer science, in order to accomplish the actual revolution, your system needs to be able to let people work in the terms they're already comfortable with: (messy world of existing programming languages) -> (your pure math) -> (messy world of hardware) But I don't think these hurdles constitute a "great filter" in the sense of the original article. Its just a quirk of human nature that the people interested in the pure math bit in the middle tend to find the messes on either side tedious and unnecessary for their insights. What essentially ends up happening is that the people who are only concerned with intellectual satisfaction get such a big dose of satisfaction from the pure math in the middle, that they never bother with the messy bits on either side. So I've found that the people who do the most impressive work have some external-to-computer-science itch they're trying to scratch. People like Christian Schafmeister[1] whose chemistry aspirations led him to create a new Lisp to glue together C++, Mathematica, Maxima, and Fortran in such a way that he can highly efficiently express and compute the math he was trying to solve. These kind of people fight through the messy world of existing languages to express the pure mathematics of their field in such a way that it can run efficiently on the messy world of hardware. [1] https://www.youtube.com/watch?v=8X69_42Mj-g#t=17m25s https://www.youtube.com/watch?v=8X69_42Mj-g#t=17m25s