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Joined 2 years ago
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Cake day: July 3rd, 2023

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  • The bar is set REALLY low

    There’s a saying “the bar for men is in hell”

    I thought it meant there was a drinking establishment for men in hell. They go and drink with the devil, and that’s where they get all their bad ideas. They’re doing shots and the devil’s like “say she’s fat”, and the guy is like “good advice bro”.

    Turns out the saying just means the bar is super low. So low you don’t even have to jump. It’s so low, it’s deeper than the depths of the earth and in the fires of hell that burn below.

    But yeah, so many men are so horrible, it’s shockingly easy to rise above them.






  • Oh yeah. Cars are bad on like every metric.

    Socially they isolate people. You don’t interact with anyone when you’re driving except to get angry. The micro interactions you have on the train matter. Seeing people that aren’t just like you, also annoyed that the train is delayed, or just having a nice time with their kids, matters. More than makes up for when other people are annoying.

    Economically they hurt. It’s much harder to just pop into an interesting looking shop when you’re cruising along at 40mph. All the space dedicated to parking could be used for other stuff- housing, commerce, communal space, whatever.

    They make spaces less safe. Other than the direct impact (no pun intended) of people getting hit by cars, or crashing into stuff, a space that has steady foot traffic is generally safer. If everyone was in their car instead, you’d probably be alone on foot with no one to help if something happened.

    They’re bad for the environment. Air pollution, micro plastics, whatever.

    Drunk driving is way more dangerous than drunk “riding the train”.

    The more non-car options are built out, the better it will be for people who need to drive for whatever reason.

    Cars culture is trash and if we ever escape from it, it’s going to take years.








  • Many people have found that using LLMs for coding is a net negative. You end up with sloppy, vulnerable, code that you don’t understand. I’m not sure if there have been any rigorous studies about it yet, but it seems very plausible. LLMs are prone to hallucinating, so you’re going to get it telling you to import libraries that don’t exist, or use parts of the standard library that don’t exist.

    It also opens up a whole new security threat vector of squatting. If LLMs routinely try to install a library from pypi that doesn’t exist, you can create that library and have it do whatever you want. Vibe coders will then run it, and that’s game over for them.

    So yeah, you could “rigorously check” it but a. all of us are lazy and aren’t going to do that routinely (like, have you used snapshot tests?), b. it’s going to anchor you around whatever it produced, making it harder to think about other approaches, and c. it’s often slower overall than just doing a good job from the start.

    I imagine there are similar problems with analyzing large amounts of text. It doesn’t really understand anything. To verify it’s correct, you would have to read the whole thing yourself anyway.

    There are probably specialized use cases that are good- I’m told AI is useful for like protein folding and cancer detection- but that still has experts (I hope) looking at the results.

    To your point, I think people are trying to use these LLMs for things with definite answers, too. Like if I go to google and type in “largest state in the US” it uses AI. This is not a good use case.