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Joined 3 years ago
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Cake day: July 1st, 2023

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  • Well “solved” is a bit of a weird way to say it. Was it proven as true, or was it disproven? Both of those change things in different ways.

    Proven true that it is a stable formula, then that’s cool, and we know that issues with fluid simulations based off of that are a software and compute problem.

    If it was disproven, then we learn precisely under what specific conditions nature becomes mathematically unpredictable, and then we can start developing different and better models.



  • I mean, screw performance. You can get away with a lot of shitty performance and still have a completely functional application. However, the kind of slop that happens around module boundaries that turns your codebase into a giant pile of workarounds and hacks really sucks.

    And AI is particularly bad at this, as AI almost always prefers to work around a problem or do everything it can to meet the plan the user approved, even if that plan meets reality, it has problems. Which tends to lead to cascading misalignment with intentions and cascading infrastructure and architectural technical debt.

    All of which culminate in less stable software, lower likelihood of long-term support of that software, and worse performance.











  • Pretty much.

    I’ve started using AI on a project last week and the first thing I do is write tests. Lots of tests.

    With enough guardrails, you could actually get pretty decent quality output out of it and with enough regression tests, you can ensure that nothing’s actually breaking.

    Similarly, reviewing its changes and actually reading the code that’s being generated to ensure correctness is necessary. However, I am finding ways to automate that and reduce the incident rate of problems to even lower than my co-workers.