• 4 Posts
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Joined 1 year ago
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Cake day: November 12th, 2024

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  • If you have a smartphone, you get to use UPI (United Payments Interface).
    If you don’t, you are basically limited to a certain amount of free withdrawal per month, which is set to prevent getting an outcry from BPL (below poverty line) people, which would otherwise be bad for elections.

    I was considering pushing for open source UPI apps for Linux devices (and providing my services for development), to reduce India’s reliance on Google and Android but considering recent events, I believe that is not really going to align with the Government’s plans.







  • ulterno@programming.devtoAsklemmy@lemmy.ml*Permanently Deleted*
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    8 days ago

    On Lemmy, you get to make your own algorithm to choose which post comes first.
    So you can even go with a most-downvotes-first approach.

    It will matter depending upon what people choose.
    The usual ones on clients[1] are Hot, Top, Controversial, New and Old and the Controversial one has to do with both, upvotes and downvotes.


    1. or is it coming from the server? Yeah, it seems to be provided by the server ↩︎




  • Yeah, my main point with all those examples was to put the point that “AI” always has been a marketing term.

    Curve-fitting and data-point clustering are both pretty efficient if used for the thing they are made for. But if you then start brute-forcing multiple nodes of the same thing just to get a semblance of something else, that is otherwise not what it is made for, of course you will end up using a lot of energy.


    We humans have it pretty hard. Our brain is pretty illogical. We then generate multiple layers of abstractions make a world view, trying to match the world we live in. Over those multiple layers, comes a semblance of logic.
    Then we make machine.

    We make machines to be inherently logical and that makes it better at logical operations than us humans. Hence calculators.
    Now someone comes and says - let’s make an abstraction layer on top of the machine to represent illogical behaviour (kinda like our brains).
    (┛`Д´)┛彡┻━┻

    And then on top of that, they want that illogical abstract machine to itself create abstractions inside it to be able to first mimic human output and then further to do logical stuff. All of that, just so one can mindlessly feed data into it to “train” it, instead of think themselves and feed it proper logic.

    This is like saying they want to install an OS on browser WASM and then install a web browser inside that OS, to do the same thing that they would have otherwise done with the original browser.

    In the monkeys analogy, you can add that the monkeys are a simulation on a computer.



  • If something uses a lot of if else statements to do stuff like become a “COM” player in a game, it is called an Expert System.
    That is what is essentially in game “AI” used to be. That was not an LLM.

    Stuff like clazy and clang-tidy are neither ML nor LLM.
    They don’t rely on curve fitting or mindless grouping of data-points.
    Parameters in them are decided, based on the programming language specification and tokenisation is done directly using the features of the language. How the tokens are used, is also determined by hard logic, rather than fuzzy logic and that is why, the resultant options you get in the completion list, end up being valid syntax for said language.


    Now if you are using Cursor for code completion, of course that is AI.
    It is not programmed using features of the language, but iterated until it produces output that matches what would match the features of the language.

    It is like putting a billion monkeys in front of a typewriter and then selecting one that make something Shakespeare-ish, then killing off all the others. Then cloning the selected one and rinse and repeat.

    And that is why it takes a stupendously disproportionate amount of energy, time and money to train something that gives an output that could otherwise be easily done better using a simple bash script.