The catarrhine who invented a perpetual motion machine, by dreaming at night and devouring its own dreams through the day.

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Joined 6 months ago
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Cake day: January 12th, 2024

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  • Those are used with urine, not blood. Urine is yellow-ish, but since it’s just a drop, it doesn’t stain the strip; instead, the blue tip changes colour as it reacts with the glucose in the urine. Then you compare that coloured tip with a chart, and you get an idea of the concentration of glucose in your body. Picture related:

    I remember seeing those bottles in my bathroom all the time as a kid (my sister is diabetic).

    These almost look more like ph or ketone test strips…

    It is roughly the same idea as the one behind the litmus test for pH, indeed. The difference is which substance you’re putting there (Benedict’s reagent vs. pH indicators) and which substance you’re testing for (glucose vs. H₃O⁺ / OH⁻).




  • The only time that I remember dreaming with my phone, I was trying to turn it off, while its real life counterpart rung furiously.

    I’ve dreamt some times with my desktop though. Such as:

    • my cat pulling out the mouse from my computer, sitting in its place on the mousepad, and then meowing loudly (she does this a lot when she’s play-hunting)
    • throwing potatoes on the screen, so I could get some French fries in return
    • keyboard gardening: the keys were subbed with small pots full of dirt, some with small versions of plants. A lot of them were pepper plants and I was trying to cross-breed them.




  • This screams FAITH (Filthy Assumptions Instead of THinking) from a distance, on multiple levels:

    1. Assuming that the current machine learning development will lead to artificial general intelligence. Will it?
    2. Assuming that said AGI would appear in time to reduce power consumption. Will it?
    3. Assuming that lowering the future power consumption will be enough to address issues caused by the current power consumption. Will it?
    4. Assuming that addressing issues from a distant future means that the whole process won’t cause harm for people in a nearer future. Will it?

    Furthermore, Gates in the quote is being disingenuous:

    “Let’s not go overboard on this,” he said. “Datacenters are, in the most extreme case, a 6 percent addition [to the energy load] but probably only 2 to 2.5 percent. The question is, will AI accelerate a more than 6 percent reduction? And the answer is: certainly,” Gates said.

    The answer addresses something far, far more specific than the main issue.


    If I may, here’s my alternative solution for the problem, in the same style as Gates’:

    Kill everyone between the North Pole and the Equator.

    What do you mean, it would kill 85% people in the world? Well, you can’t make an omelet without breaking some eggs, right? Nobody that I know personally lives there, so Not My Problem®. (Just keep Japan, I need my anime to watch.)

    …I’m being clearly sarcastic to deliver a point here - it’s trivially easy to underestimate issues affecting humankind, and problems associated with their solutions, if you are not directly affected by either. Gates is some billionaire bubbled around rich people; this sort of problem will affect the poor first, as the rich can simply throw enough money into their problems to make them go away.





  • Is it? [coherent]

    Yes when it comes to the relevant info. The anaphoric references are all over the place; he, her, she, man*, they all refer to the same fossil.

    *not quite an anaphoric reference, I know. I’m still treating it as one.

    I can only really guess whether they’re talking about one or two subjects here.

    It’s clearly one. Dated to be six years old, of unknown sex, nicknamed “Tina”.

    Why does it show someone cared for the mother as well?

    This does not show lack of coherence. Instead it shows the same as the “is it?” from your comment: assuming that a piece of info is clear by context, when it isn’t. [This happens all the time.]

    That said, my guess (I’ll repeat for emphasis: this is a guess): I think that this shows that they cared for the mother because, without doing so, the child would’ve died way, way earlier.

    That all reads like bad AI writing to me.

    I genuinely don’t think so.

    Modern LLMs typically don’t leave sentence fragments like “on the territory of modern Spain. Years ago.” They’re consistent with anaphoric references, even when they don’t make sense in the real world. And they don’t screw up with prepositions, like switching “in” with “on”. All those errors are typically human.

    On the other hand, LLMs fail hard on a discursive level. They don’t know the topic (in this case, the fossil). At least this error is not present here.

    Based on that I think that a better explanation for why this text is so poorly written is “CBA”. The author couldn’t be arsed to review it. Myself wrote a lot of shit like this when drunk, sleepy, or in a rush.

    I’ll go a step further and say that the author likely speaks more than one language, and they were copying this stuff from some site in another language that has grammatical gender. I’m saying this because it explains why the anaphoric references are all over the place.



  • If I were to watch Dragon Ball Z now, I’d probably drop the series. I still remember it fondly, but it’s too slow.

    The first two seasons of the Pokémon anime aged well for me. Individual games, too. But the series as a whole felt from an “I know all 386!” to “…it’s a Tentaquil”.

    Chrono Trigger went from “it’s okay, it’s fun” to “…I spent my whole life underrating it, didn’t I?” So did Final Fantasy VI.

    Same deal with Dostoyevsky. I guess you need some maturity to understand things.

    Baudelaire, though? Hard pass.

    I still love 1984 and Animal Farm, but I want to drown 90% of the muppets talking about them.

    I can’t stand Legião Urbana any more. Pink Floyd on the other hand aged well, so did Nenhum de Nós.

    To be honest I was never too much into movies. There’s one or another thing that I like (Modern Times, 8 1/2, The Shining), but it’s mostly unchanged.


  • Those mistakes would be easily solved by something that doesn’t even need to think. Just add a filter of acceptable orders, or hire a low wage human who does not give a shit about the customers special orders.

    That wouldn’t address the bulk of the issue, only the most egregious examples of it.

    For every funny output like “I asked for 1 ice cream, it’s giving me 200 burgers”, there’s likely tens, hundreds, thousands of outputs like “I asked for 1 ice cream, it’s giving 1 burger”, that sound sensible but are still the same problem.

    It’s simply the wrong tool for the job. Using LLMs here is like hammering screws, or screwdriving nails. LLMs are a decent tool for things that you can supervision (not the case here), or where a large amount of false positives+negatives is not a big deal (not the case here either).




  • All languages are the result of the collective brainfarts of lazy people. English is not special in this regard.

    What you’re noticing is two different sources of new words: making at home and borrowing it from elsewhere.

    For a Germanic language like English, “making at home” often involves two things:

    • compounding - pick old word, add a new root, the meaning is combined. Like “firetruck” - a “truck” to deal with “fire”. You can do it recursively, and talk for example about the “firetruck tire” (the space is simply an orthographic convention). Or even the “firetruck tire rubber quality”.
    • affixation - you get some old word and add another non-root morpheme. Like “home” → “homeless” (no home) → “homelessness” (the state of not having a home).

    The other source of vocabulary would be borrowings. Those words aren’t analysable as the above because they’re typically borrowed as a single chunk (there are some exceptions though).

    Now, answering your question on “why”: Norman conquest gave English a tendency to borrow words for “posh” concepts from Norman, then French. And in Europe in general there’s also a tendency to borrow posh words from Latin and Greek.