Profile pic is from Jason Box, depicting a projection of Arctic warming to the year 2100 based on current trends.

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Cake day: March 3rd, 2024

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  • It was fun to learn how things work, and when things worked as planned (finally). It’s when they didn’t work that got annoying and frustrating, and with assembly language with basically no error codes or any help, it was just…nope, that wasn’t right. Maybe followed by cycling the computer off and on because it locked up. Still have my old Mapping the Commodore 64 book on the shelf. Huge resource.








  • I don’t know… the Moon is beautiful, but George Carlin had a point on worshiping the Sun:

    “I’ve begun worshiping the sun for a number of reasons. First of all, unlike some other gods I could mention, I can see the sun. It’s there for me every day. And the things it brings me are quite apparent all the time: heat, light, food, and a lovely day. There’s no mystery, no one asks for money, I don’t have to dress up, and there’s no boring pageantry. And interestingly enough, I have found that the prayers I offer to the sun and the prayers I formerly offered to ‘God’ are all answered at about the same 50% rate.”


  • No one mentioned (probably an assumed thing) to turn the water on full hot to let it warm up, then move it to the preferred mix position. Doesn’t waste the cold water which will stay more or less the same temp, it’s only flushing out the cold in the hot water line. And because you have it fully on hot, it takes less time.

    Or get a tankless water heater to get it almost right away. I’ve seen debates on which is a better choice when factoring everything in, and I think it’s a close tie with no clear winner, each having their caveats.





  • LLMs can be good at openings. Not because it is thinking through the rules or planning strategies, but because opening moves are likely in most general training data from various sources. It’s copying the most probable reaction to your move, based on lots of documentation. This can of course break down when you stray from a typical play style, as it has less to choose from in the options of probability, and only a few moves in there won’t be any more since there’s a huge number of possible moves.

    I.e., there’s no calculations involved. When you play a LLM at chess, you’re playing a list of common moves in history.

    An even simpler example would be to tell the LLM that its last move was illegal. Even knowing the rules you just told it, it will agree and take it back. This comes from being trained to give satisfying replies to a human prompt.