Charlie Loyd @vruba@everything.happens.horse

This is, to be clear, me subtweeting people getting mad at ChatGPT for using a modest amount of water compared to … almost anything else you could name? Every single almond, like literally one lone almond, is about 3,000 ml of virtual water. A cup of coffee is 100,000+ ml; pee it out into a high-efficiency toilet and that’s a minimum 4,000 ml flush. May I suggest that the rogue billionaires explicitly aiming to stop paying for labor are the problem to focus on here.

Opinions my grandparent had about cars, c. 2000 CE:

1. Electric cars are wildly dangerous because you can’t hear them coming; they will kill dozens of times as many people as gas cars do.

2. It’s hard to get across town these days what with all the traffic caused by big busses.

3. The New Beetle should be banned from public roads since it’s front/back symmetrical: you can’t tell which way it’s going.

Cars are in fact bad but not really for any of those reasons. I remember this sometimes.

@kgjenkins https://extension.psu.edu/plastic-wrapped-hay-bale-research ?

@sgillies I feel like a lot of people are responding to gerontocracy (bad but easily solvable) with ageism (bad and hard to root out) and it’s a pity.

@midendian Yeah, this example is cherry-picked for minimal camera shake, and I downsampled before doing anything, and I’m pretty sure you can still find shake-induced artifacts if you look.

And I should say: the way this actually works in practice is you take the timeseries of each pixel in the video, in oklab or your preferred color space, and do an interquartile (or similarly trimmed) mean on it.

Anyway, the trick is, you take a low discrepancy sequence on a sphere (I used R[2] and a Lambert azimuthal projection) and use those angles as lines to sample depth – a measure of centrality – along; you map these angle samples over your points and reduce with min(), and you get an approximation of Tukey’s multivariate depth, which is a generalization of the median (or quantile). I may explain this better eventually but then again I may not.

A wonderful thing about image processing is you’re always discovering completely new and fascinating ways to make pictures look worse.

Made a little thing to take fast approximate multivariate medians, at no small cost to my sanity, and it turns out that when I apply it to pixels in California Landscapes time lapse videos (e.g., https://onewilshire.la/@CALandscapeBot/110699293237082262) it’s mostly just Compression Artifact Finder 2023 Pro Edition.

@nelson “Solarpunk company town, right-wing ecosocialism, green anarchism but owned by VCs, exquisite 4K detail, trending on ArtStation”?

Partly I think the Anti faction seems to be doing a reasonable job of shifting from a “say scary and sweeping things at random to see what sticks” to “let’s try to articulate what actually concerns us here”, and that’s good. I am still not a card-carrying member of that camp, but I think it’s being a lot more honest now than it was in March, and I respect that.

I still think the discourse around LLMs right now is bad. By which I mean: most of the stuff I see on my feeds, boosted by people I like and whose ideals I tend to share, seems intellectually lazy, politically shortsighted, rhetorically misdirected, etc., in ways worse than we accept on other topics.

And yet! The average quality has gone way up over the last few months. And that gives me some hope.

@urschrei @hans Ooh, will have to pick it up.

@migurski These are they.

@migurski https://en.wikipedia.org/wiki/Surface_plate#History