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  1. Jul 2022
    1. von neumann was furious at him furious that he would waste precious machine time 00:04:20 doing the assembly that was clerical work that was supposed to be for people right and so we saw the same story happened just a little bit later when john backus and friends came up with us idea they called fortran this is so call high-level language where you could write out your formulas as if your writing mathmatical notation you could write out loops and this was shown to the assembly programmers and once again they just 00:04:46 they weren't interested they don't see any value in that they just didn't get it so um I want you to keep this in mind as I talk about the four big ideas that I'm going to talk about today that it's easy to think that technology technology is always getting better because Moore's law because computers are getting always more capable but ideas that require people to unlearn what they've learned and think in new ways there's often 00:05:10 enormous amount of resistance people over here they think they know what they're doing they think they know a programming is this programming that's not programming and so there's going to be a lot of resistance to adopting new ideas

      Cumulative cultural learning seems to be stuck in its own recursive loop- the developers of the old paradigm become the old "guard", resistant to any change that will disrupt their change. Paradigm shifts are resisted tooth and nail.

  2. Apr 2020
    1. Since we have much faster CPUs now, numerical calculations are done in Python which is much slower than Fortran. So numerical calculations basically take the same amount of time as they did 20 years ago.

      Python vs Fortran ;)

  3. Sep 2015
    1. One explanation often given is the huge amount of scien-tific legacy code in the world—after all, differential equa-tions remain the same over time and so do their solvers, sothere’s no reason to rewrite such code. But a great deal ofnew code is written in Fortran95 as well. One of us recentlyserved on a review panel for granting computer time tohigh-impact scientific computing applications that effec-tively use thousands of processors, and every single one ofthe applications he reviewed was written in Fortran. At lastyear’s conference on computational physics in South Korea(CCP2006), most of the plenary speakers who talked aboutcodes used Fortran. Perhaps scientists prefer Fortran be-cause they’re productive when using it

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