They/Them, agender-leaning scalie.

ADHD software developer with far too many hobbies/trades: AI, gamedev, webdev, programming language design, audio/video/data compression, software 3D, mass spectrometry, genomics.

Learning German (B2), Chinese (HSK 3-4ish), French (A2).

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Joined 1 year ago
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Cake day: June 18th, 2023

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  • There’s a weird divide between self-determined identity and external classifications. Often, a culture forms around the label and the external label stops being relevant because the term has more social/cultural implications than practical implications. Some people internalize the label as that’s how they wish to steer their future interactions, and others ignore the label and move on with their lives.

    You can watch all of Star Trek, and some parts of society will label you a Trekkie if they find out, but it’s up to you whether you choose to identify as a Trekkie, or just go about your life not making a big deal about it.


  • Assuming enthusiastic consent, good faith, and that you meant “sex/body they want” instead of “gender they want” (because gender is just a social construct):

    On another hand, it would erase their identity as trans people.

    I don’t think it would. Identities are built from life experiences, and having lived through transition they’d still be trans even if there were no traces of it on their body. A war veteran doesn’t stop being a veteran just because the war ended.

    consider it a genocide

    The definition of genocide depends on intent! Even in wars, etc. It’s only genocide if you’re specifically trying to erase/displace people/culture.

    • Trying to cure gender dysphoria: it’s not genocide, it’s medical treatment.

    • Trying to “fix” people to make them fit into society: it’s genocide.

    turning them into what they want would mean there is no more trans people

    There are identities that don’t stop being trans even if you give them the body they want:

    • A non-binary person’s desired sex/body and social gender might not match. Even with the perfect body (if one exists), they might still identify as trans because that body doesn’t match their social gender.

    • For genderfluid people, there might not be one singular perfect body. Even if their body constantly updated to suit them, they’d probably still identify as trans because they’d be constantly transitioning…








  • Honestly, I don’t think that there’s room for a competitor until a whole new paradigm is found. PyTorch’s community is the biggest and still growing. With their recent focus on compilation, not only are TF and Jax losing any chance at having an advantage, but the barrier to entry for new competitors is becoming much higher. Compilation takes a LOT of development time to implement, and it’s hard to ignore 50-200% performance boosts.

    Community size tends to ultimately drive open source software adoption. You can see the same with the web frameworks - in the end, most people didn’t learn React because it was the best available library, they learned it because the massive community had published so many tutorials and driven so many job adverts that it was a no-brainer to choose it over Angular, Vue, etc. Only the paradigm-shift libraries like Svelte and Htmx have had a chance at chipping away at React’s dominance.


  • The easiest way to get the basics is to search for articles, online courses, and youtube videos about the specific modules you’re interested in. Papers are written for people who are already deep in the field. You’ll get there, but they’re not the most efficient way to get up to speed. I have no experience with textbooks.

    It helps to think of PyTorch as just a fancy math library. It has some well-documented frameworky structure (nn.Module) and a few differentiation engines, but all the deep learning-specific classes/functions (Conv2d, BatchNorm1d, ReLU, etc.) are just optimized math under the hood.

    You can see the math by looking for projects that reimplement everything in numpy, e.g. picoGPT or ConvNet in NumPy.

    If you can’t get your head around the tensor operations, I suggest searching for “explainers”. Basically for every impactful module there will be a bunch of “(module) Explained” articles or videos out there, e.g. Grouped Convolution, What are Residual Connections. There are also ones for entire models, e.g. The Illustrated Transformer. Once you start googling specific modules’ explainers, you’ll find people who have made mountains of them - I suggest going through their guides and learning everything that seems relevant to what you’re working on.

    If you’re not getting an explanation of something, just google and find another one. People have done an incredible job of making this information freely accessible in many different formats. I basically learned my way from webdev to an AI career with a couple years of casually watching YouTube videos.





  • Some minor/hard-to-notice health-related things can dramatically reduce alcohol tolerance and/or give “hangovers” shortly after starting a session.

    For me, inflammation is a big cause. I have (barely noticeable) cat allergies, and (obvious but hard to avoid) food intolerances & gut issues. If I don’t stay on top of avoiding triggers, my alcohol tolerance goes from multiple G&Ts giving a nice buzz, to 1-2 sips of G&T giving dizziness and headaches. Electrolyte imbalance can also cause it. I’ve found I have to add magnesium and potassium salt to my diet, or else I generally feel tired more, and my alcohol tolerance plummets. Once you start controlling these factors, you’ll start getting clear feedback from your body when you have too much or too little salt, in the form of water and food tasting different and general feelings of tension or tiredness.

    My advice: try antihistamines, easily-digestible meals, and/or sports drinks for a few days before you drink. If those help your tolerance, you probably have some health stuff going on - figure it out and you’ll probably find a way to generally feel better.


  • ooo, I love this. It reminds me of how nice C#'s LINQ is…

    “Pipeline style” DB queries have some interesting advantages as well:

    • It’s straightforward to write efficient queries for DBs that don’t include a query optimizer stares at Datomic
    • You can split the pipeline into server-side and client-side steps when working with less capable DBs stares at most of NoSQL
    • It would be much easier to transition from a pipeline API to a non-text-based API so that our ORMs/query builders can directly talk to DBs without the overhead of generating and parsing SQL.

  • I still use Google for ~95% of my queries because I like real sources, comprehensive documentation, and not having to read a wall of text when a one-line answer would have sufficed.

    ChatGPT is a good replacement for Quora/Stack Exchange for explaining general knowledge stuff like other languages’ grammar and simple science, as well as finding authors/books/movies from descriptions when you’ve forgotten their names.

    Bard is… kinda dumb. I gave it a few chances, but it was nothing compared to ChatGPT’s free tier.