Skip Navigation

InitialsDiceBearhttps://github.com/dicebear/dicebearhttps://creativecommons.org/publicdomain/zero/1.0/„Initials” (https://github.com/dicebear/dicebear) by „DiceBear”, licensed under „CC0 1.0” (https://creativecommons.org/publicdomain/zero/1.0/)WO
Posts
17
Comments
719
Joined
2 yr. ago

  • The irony of someone with the handle anticolonialist spouting talking points in favour of an imperialist land grab where they are literally creating colonies of Russians along the corridor of Ukrainian land between Russia and Crimea is just beautiful.

  • Look, Putin has been very clear that he wants peace. All Ukraine have to do is surrender and pull out of the quarter of their country that Russia has "Annexed" while not in control of. Then peace negotiations can begin as to what else Ukraine has to give up in order for the fighting to not resume.

    (Note, not sarcasm, this actually the offer Russia has given for a ceasefire, not even peace terms)

  • To put a bit of context on those, 50GWh is a single medium sized power station running for 2 days. To create something that is being used around 10 million times a day all over the world.

    At 10 million queries per day that puts the usage per query at 100-500 Wh, about the amount of energy used by leaving an old incandecent lightbulb on for an hour, or playing a demanding video game for about 20 minutes.

    As another comparison, In the USA alone around 12,000 GWh of energy is spent in burning gasoline in vehicles every single day. So Americans driving 1% less for a single day would save more energy than creating GPT4 and the world using it for a year.

  • I was responding to your general statement that python is slow and so there is no point in making it faster, I agree that removing the GIL wont do much to improve the execution speed for programs making heavy use of numpy or things calling outside it.

    That’s a bit suss too tbh. Did the C++ version use an existing library like Eigen too or did they implement everything from scratch?

    It was written entirely from scratch which is kind of my point, a well writen python program can outperform a naive c implementation and is vastly simpler to create.

    If you have the expertise and are willing to put in the effort you likely can squeze that extra bit of performance out by dropping to a lower level language, but for certain workloads you can get good performance out of python if you know what you are doing so calling it extremely slow and saying you have to move to another language if you care about performance is missleading.

  • Numpy is written in C.

    Python is written in C too, what's your point? I've seen this argument a few times and I find it bizarre that "easily able to incorporate highly optimised Fortran and C numerical routines" is somehow portrayed as a point against python.

    Numpy is a defacto extension to the python standard that adds first class support for single type multi-dimensional arrays and functions for working on them. It is implemented in a mixture of python and c (about 60% python according to github) , interfaces with python's c-api and links in specialist libraries for operations. You could write the same statement for parts of the python std-lib, is that also not python?

    Its hard to not understate just how much simpler development is in numpy compared to c++, in this example here the new python version was less than 50 lines and was developed in an afternoon, the c++ version was closing in on 1000 lines over 6 files.

  • Nope, if you're working on large arrays of data you can get significant speed ups using well optimised BLAS functions that are vectorised (numpy) which beats out simply written c++ operating on each array element in turn. There's also Numba which uses LLVM to jit compile a subset of python to get compiled performance, though I didnt go to that in this case.

    You could link the BLAS libraries to c++ but its significantly more work than just importing numpy from python.

  • Python can be extremely slow, it doesn't have to be. I recently re-wrote a stats program at work and got a ~500x speedup over the original python and a 10x speed up over the c++ rewrite of that. If you know how python works and avoid the performance foot-guns like nested loops you can often (though not always) get good performance.

  • Biggest reason Linux fails where Windows 11 sucseeds is because the vast VAST majority cannot figure out linux’s user experience.

    Nope, the bigest reason why windows is more popular than linux is the same as youtube is more popular than peertube - its the default and most people dont look past that. Honestly default Gnome UX is better than win11 these days unless you already have thousands of hours of windows muscle memory, which a very large chunk of people do.

  • Funadmentally it makes sense that tax take is 0 at 0% and low (though not neccessarily 0) at 100%, but in practice it only ever used to advocate for lowering taxes no matter what they are set at currently. You never see people talking about governments being on the left side of the Laffer curve and therfore we should raise taxes.

    There's also no evidence that I'm aware of that the curve is smooth, single peaked or even single valued and it is also likely highly dependent on myriad other factors, in short it's effectively useless except as a rhetorical device for small-staters to advocate slashing taxes and public services.

  • Because they are not trying to design an efficient system. They are trying to design a system that is as cheep as possible, puts off as many customers as possible from interacting with it while not being so bad as to fall foul of regulations. A well designed website that efficiently took you to the right place to make your complaint and get money from them/make them do something would fail requirement 2.

  • Yes? As I said they have a wide range of views giving comment. Just because it isnt Pravda doesnt mean its exclusively neoliberal. For example you'll be hard pressed to find any opinion pieces favourable to privatisation and public sector cuts which are two of the chief pillars of neo-liberal orthodoxy.