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Joined 3 years ago
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Cake day: June 19th, 2023

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  • Scammer reads p-chip patent, realises there’s only a small range of laser diode wavelengths that can penetrate cheese. Buys chipped cheese, breaks the cheese. Chipped pieces found using laser excitation pulse and sensor with a notch filter. Save the wedge with the most chips to repeatedly break down to get chipped cheese crumbs, insert into bogus wedges, profit.

    I’m sure the idea can be refined, but I’ll leave the fine details to the dairy delinquent curd counterfeiters.


  • Split pea and lentil soup. Get dried green split peas and dried red lentils. Put them in a pot, pour in water, add stock or salt and some dried parsley and thyme, bring to a boil then simmer for 1~1.5 hours.

    Cheap, filling, healthy, and a lot of filler ingredients work in it if you want to change it up. I’m recovering from a crushed ankle, on a crutch so I’ve had to figure out one handed recipes to a degree.

    Another good one if you have a rice cooker - coconut milk, lime juice, peanut butter and some sugar. Melt it all together, have it on rice. Again, something that’s adaptable for adding other ingredients.




  • I’m going to throw my own thoughts in on this. I got into machine learning around 2015, back when relu activations were still bleeding edge innovations, and got out around 2020 for honestly pretty similar reasons.

    Emotions can and have been used as optimisation targets. Engagement is an ever present target. And in the framework of capitalism, one optimisation targets rules above all others; alignment with continued use. It’s part of what leads to the bootlicking LLM phenomenon. For the average human, it drives future engagement.

    The real danger isn’t the newer language models, or anything really to do with neural net architecture; rather, it’s the fact that we’ve found that a simple function minimisation strategy can be used to approximate otherwise intractable functions. The deeper you research, the more clear it becomes that any arbitrary objective can be optimised, given a suitable function approximator and enough data to fit the approximator accurately.

    Human minds are also universal function approximators.












  • Make bread, cook bread. Put some bread in water, let it get the funny mold. Cook the rest so it’s toasty. Strain the moldy bread water, chill the bread water. Cook down the bread soup gunk until it’s a paste, smear it on the cooked cooked bread and drink the bread water.

    Vegemite on toast with a beer on the side is weird when you spell it out.