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Cake day: November 1st, 2026

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  • I sometimes visit TikTok like twice a year just to understand what type of media your average Joe/Jane consumes. My conclusion is that it’s mindless and overly rapid content that does not sticks in the head. I could not recall anything I’ve consumed the day after.

    But honestly it’s not THAT different from watching TV/YT all night, or scrolling reddit/lemmy. I cannot recall what content I’ve consumed yesterday, maybe only small pieces here and there, despite watching “intelligent” content like documentaries & video essays or reading articles & news. To my brain it was simply entertainment just for that moment. A waste of my precious life.

    We all consume, but few of us create.








  • In my OP, I did not mean specifically some LLM, but a hypothetical, scalable-past-human-capabilities synthetic brain.

    Today it is a statistical model

    I would argue that a human brain is a statistical model. Complex, but in the end it’s a black box that takes in input from senses, and spits out output in form of interaction with environment. I’m not saying we and LLMs are in any way alike, or that AI is alive. But I do not agree with postulation that a true artificial thinking machine is impossible to build within next 1B years or however long Earth stays habitable for complex life.






  • It doesn’t know what red is. It doesn’t know what a dog is

    This is very philosophical, but what is understanding of something? Isn’t it just relationships between different concepts? LLM currently encode information similarly in their multidimensional vector space. Where a “dog” vector would be close to “animal” “pet” “breed” etc vectors and those in turn to other similar concepts and so on. How different is it from human way of understanding?

    LLMs cannot do that. LLMs have to be retrained with data in a very specific format from the start

    Sure, that is true right now. But in not-so-distant future, it is not unreasonable to assume AI would be able to improve itself without as much (or any) human intervention. For example it could streamline training, automatically collect new data from across the world in real time. Be able to access its own weights in the model, increase improvement efficiency possibly exponentially even.