cmfhsu

@cmfhsu@lemmy.world

• ⁨Comment⁩ on ⁨when gf is a mechanic⁩ ⁨⁨2⁩ ⁨months⁩ ago⁩:

  Oh yeah for sure. I’m just a home gamer and I can’t stand jumpsuits, so any axle grease or bearing grease turns me into a spec ops camouflage expert

• ⁨Comment⁩ on ⁨when gf is a mechanic⁩ ⁨⁨2⁩ ⁨months⁩ ago⁩:

  Yeah, I’m pretty sure that’s for rotating the inner tie rod when adjusting toe, not for replacing the inner - though I do love purpose made tools.

  I do a lot of track days and racing, so my toolkit is usually pretty minimal since I don’t own a semi to haul my tools over. My rule is usually “make do with what you have twice. If you’re still swearing the second time, go buy a quality dedicated tool and find room in the mobile tool box”.

• ⁨Comment⁩ on ⁨when gf is a mechanic⁩ ⁨⁨2⁩ ⁨months⁩ ago⁩:

  Oof. What if I don’t want to buy a 33mm wrench for the one inner tie rod I’ll do in five years?

  Tub o towels is the most magical product I’ve ever discovered for people to do automotive work. I could bathe in that stuff

• ⁨Comment⁩ on ⁨Go already⁩ ⁨⁨2⁩ ⁨months⁩ ago⁩:

  Not sure what the problem is. Keep doing it.

  This is how I operate in most traffic jams, since I only own manual cars & it’s much easier on my leg.

  I genuinely don’t even remember any specific scenarios where somebody merging in caused me to have to come to a full stop (where I wouldn’t have had to stop if they didn’t merge). Not saying it never happened, but it was so rare and unnotable that I don’t remember.

  I do live in the northeast US, so maybe that has something to do with it, but I don’t usually feel like I spend meaningfully more time in traffic because I let a few people in front of me.

  Bonus benefit: my life is measurably better since I stopped getting pissed about people being in front of me. Road rage had such a broad impact on me, even after I got out of the car.

• ⁨Comment⁩ on ⁨OpenAI confirms that AI writing detectors don’t work⁩ ⁨⁨1⁩ ⁨year⁩ ago⁩:

  In statistics, everything is based off probability / likelihood - even binary yes or no decisions. For example, you might say “this predictive algorithm must be at least 95% statistically confident of an answer, else you default to unknown or safe answer”.

  What this likely means is only 23% of the answers were confident enough to say “yes” (because falsely accusing somebody of cheating is much worse than giving the benefit of the doubt) and were correct.

  There is likely a large portion of answers which could have been predicted correctly if the company was willing to chance more false positives (potentially getting studings mistakenly expelled).