Poik
Or use it on large scale computing for protein folding simulations, or something.
And yeah, gravity batteries is the best I think we have, with water being the most common medium with pumped-storage hydroelectricity. But the scales of the things are kind of incongruent and... Autoincorrect actually got it right trying to correct that to inconvenient. Still really cool. I think we may need some innovations to cut down on scale issues though. Although it looks like the total power storage available is about one day worth of power for the US in PSH, I'm curious if the instantaneous output is sufficient for the grid and how spread out the storage locations are, as I somewhat doubt they're often in flatter regions. All in all, I'm not a power engineer, I just know a few and I should bug them sometime.
I wish I could taste the other flavors. That's actually why I was considering desensitizing myself to it. I get the dirt and earthy, but I love both of those the same. I've been growing my palette, but it took me nearly two decades to find hops that I could stand to start desensitizing myself to that bitter.
I mean... It's literally genetic. The aldehydes in cilantro usually aren't strong enough for people to taste. But if you want to know what I taste when I eat cilantro, go crush a stink bug, it's the same chemical.
Apparently I can desensitize myself to it, and I want to. Certainly would open up a lot of options in foods I'm already a fan of (if you leave out the cilantro).
That... Doesn't align with years of research. Data is king. As someone who specifically studies long tail distributions and few-shot learning (before succumbing to long COVID, sorry if my response is a bit scattered), throwing more data at a problem always improves it more than the method. And the method can be simplified only with more data. Outside of some neat tricks that modern deep learning has decided is hogwash and "classical" at least, but most of those don't scale enough for what is being looked at.
Also, datasets inherently impose bias upon networks, and it's easier to create adversarial examples that fool two networks trained on the same data than the same network twice freshly trained on different data.
Sharing metadata and acquisition methods is important and should be the gold standard. Sharing network methods is also important, but that's kind of the silver standard just because most modern state of the art models differ so minutely from each other in performance nowadays.
Open source as a term should require both. This was the standard in the academic community before tech bros started running their mouths, and should be the standard once they leave us alone.
In the US, in most states, getting caught or recognized is enough to put you on the sex offender list. Even if you're in private. (Again, in most states.) And that means you can no longer move into a new home without informing all your neighbors that you're a sex offender for the rest of your life, among other penalties. There's no difference to the US between this and people who actually do sexual crimes when it comes to this punishment.