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Joined 1 year ago
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Cake day: July 27th, 2023

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  • I’d be interested in setting up the highest quality models to run locally, and I don’t have the budget for a GPU with anywhere near enough VRAM, but my main server PC has a 7900x and I could afford to upgrade its RAM - is it possible, and if so how difficult, to get this stuff running on CPU? Inference speed isn’t a sticking point as long as it’s not unusably slow, but I do have access to an OpenAI subscription so there just wouldn’t be much point with lower quality models except as a toy.




  • Well they said .NET Framework, and I also wouldn’t be surprised if they more or less wrapped that up - .NET Framework specifically means the old implementation of the CLR, and it’s been pretty much superseded by an implementation just called .NET, formerly known as .NET Core (definitely not confusing at all, thanks Microsoft). .NET Framework was only written for Windows, hence the need for Mono/Xamarin on other platforms. In contrast, .NET is cross-platform by default.





  • This is a use-after-free, which should be impossible in safe Rust due to the borrow checker. The only way for this to happen would be incorrect unsafe code (still possible, but dramatically reduced code surface to worry about) or a compiler bug. To allocate heap space in safe Rust, you have to use types provided by the language like Box, Rc, Vec, etc. To free that space (in Rust terminology, dropping it by using drop() or letting it go out of scope) you must be the owner of it and there may be current borrows (i.e. no references may exist). Once the variable is droped, the variable is dead so accessing it is a compiler error, and the compiler/std handles freeing the memory.

    There’s some extra semantics to some of that but that’s pretty much it. These kind of memory bugs are basically Rust’s raison d’etre - it’s been carefully designed to make most memory bugs impossible without using unsafe. If you’d like more information I’d be happy to provide!





  • I was very intrigued by a follow-up to the recent numberphile video about divergent series. It was a return to the idea that the sum of the integers greater than zero can be assigned the value -1/12. There were some places this could be used, but as far as I know it was viewed as shaky math by a lot of experts.

    As far as I recall the story goes something like this: now, using a new technique Terrence Tao found, a team was seemingly able to “fix” previous infinities in quantum field theory - there’s a certain way to make at least some divergent series work out to being a real number, and the presenter proposed that this can be explained as the universe “protecting us” from the infinities inherent in the math.

    It made me think about other places infinities show up in modern physics (namely, singularities in general relativity) and whether a technique something like this could “solve” them without a whole new framework like string theory is.



  • The issue is that, in the function passed to reduce, you’re adding each object directly to the accumulator rather than to its intended parent. These are the problem lines:

    if (index == array.length - 1) {
    	accumulator[val] = value;
    } else if (!accumulator.hasOwnProperty(val)) {
    	accumulator[val] = {}; // update the accumulator object
    }
    

    There’s no pretty way (that I can think of at least) to do what you want using methods like reduce in vanilla JS, so I’d suggest using a for loop instead - especially if you’re new to programming. Something along these lines (not written to be actual code, just to give you an idea):

    let curr = settings;
    const split = url.split("/");
    for (let i = 0; i < split.length: i++) {
        const val = split[i];
        if (i != split.length-1) {
            //add a check to see if curr[val] exists
            let next = {};
            curr[val] = next;
            curr = next;
        }
        //add else branch
    }
    

    It’s missing some things, but the important part is there - every time we move one level deeper in the URL, we update curr so that we keep our place instead of always adding to the top level.