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  • The ingestion/breathability table might be more restrictive. Like, elemental Sulfur is perfectly fineno actually it’s not fine— but probably unpleasant to lick. Contact dermatitis likely but not life threatening—just one lick, ok; promise no more? ;)

    Breathing elemental Sulfur is also going to result in contact dermatitis -inside the lungs. Which is going make a really bad day.

  • Sometimes old software just has too much legacy spaghetti written in to really build from though. Starting from scratch gives new ideas room to breathe and grow that might otherwise be impossible to implement in the previous framework—which while probably useful can also be stifling. See the reason why Wayland is being written to replace Xorg.

  • 1 if that is Emperor Georgiou. The shit talking would be nonstop entertainment and I’m all in for that. Well, she might kill me, but that’s not a bad way to get out of a 12 hour shuttle trip.

    Edit. Fuck, she might put me in an agonizer when we arrive. Maybe this isn’t the right path. But she is super hot and interesting so maybe still worth.

  • I don’t think an SSD is the right choice here. SSDs have a limited lifespan that’s majority driven by the number of writes that happen to a certain block. Reads are cheap and near infinite though.

    When you’re talking about a Lemmy instance, mail server, etc. my mind thinks this is likely to be many writes with several read-once ops. This is a better use case for a HDD.

    A media server that oriented towards most consumption (reading) would be better for SSD.

  • She’s a firebrand—that’s not an insult. But it is a fact that if the DNC puts her to run, she will mobilize a lot of voters who may otherwise sit this one out. Hard to say definitively how many on either side; but I think she’s likely more hated by the rightwing base than she is loved by the left wing/centrist base.

    I don’t think it would be a good strategic move in this cycle. Although I’d love to see her in the Oval Office and would vote that way should the chance arise.

  • As I was reading your comment I was thinking Physics Informed NN’s and then you went there. Nice. I agree.

    I’ve built some models that had a solution constrained loss functions—featureA must be between these values, etc. Not quite the same as defining boundary conditions for ODE/PDE solutions but in a way gets to a similar space. Also, ODE/PDE solutions tend to find local minima and short of changing the initial conditions there aren’t very many good ways of overcoming that. Deep learning approaches offer more stochasticity so converge to global solutions more readily (at the risk of overfitting).

    The convergence of these fields is exciting to watch.

  • How is it different than using numerical methods to find solutions to problems for which analytic solutions are difficult, infeasible, or simply impossible to solve.

    Any tool that helps us understand our universe. All models suck. Some of them are useful nevertheless.

    I admit my bias to the problem space though: I’m an AI engineer—classically trained in physics and engineering though.