Not just not accurate but wrong.

That's like saying the price of the battery in an electric car is that car's price minus the price of a comparable ICE car. No, it isn't. There are more differences than just the battery.

And yes, of course they recoup their development costs. But that doesn't mean that the OP is right in this context.

Nuclear reactors use most surface water, not ground water.

Datacentres are no pickier. You can even cool a datacentre with saltwater, you just need a heat exchanger.

Also, closed loop does not evaporate. The loop is not closed if stuff escapes from it.

You're arguing with the actual terminology used in the nuclear industry. "Closed loop" or "closed cycle" designs have the water pumped in a cycle through cooling towers. The towers lose water to evaporation, taking heat with them, but the rest of the water is returned to be reheated again. "Open loop" or "open cycle" designs have no cooling towers. The water is heated and just discharged hot. They consume much more water (over an order of magnitude more), but most of that is returned. Closed loop are more common, but you see open loop in some older designs, and in seawater-cooled reactors.

"How often do you think I print?"

Seemingly not very.

I've printed many hundreds of kg on my P1S, thanks.

I do not consider having to write data out to a card and transport it back and forth between the printer and the computer to be the pinnacle of convenience. That's something that would be considered embarrassingly inconvenient for a 1980s printer, let alone a modern net-connected device. And it's designed to be inconvenient for non-cloud prints for a reason.

errr... Apple doesn't charge for its operating system. macOS literally doesn't have a price.

Also, anything sounds big when you put it in gallons. Doesn't sound so big when you mention that's 92 acre feet, the amount used by less than 20 acres / 8 hectares of alfalfa per year. Or when you mention that a typical *closed loop* 1GW nuclear reactor uses 6-20 billion gallons of cooling water per year (once-through uses 200-500 billion gallons, though most of that is returned, whereas closed loop evaporates it)

I don't think it has anything to do with that. As soon as I saw the headline, my mind went "cohort study". And sure enough, yeah, it's a cohort study. Remember that big thing about how wine improves your health, and then it turned out to just be that people who drink wine tend to be wealthier and thus have better health outcomes? And also, the "sick quitter" effect, where people who are in worse health would tend to stop drinking, so you ended up with extra sick people in the non-wine group? Same sort of thing. This study says they're controlling for a wide range of factors, but I'd put money on it just being the same sort of spurious correlations.

"I just put my models on a usb drive then plug said drive into the printer."

You must have a lot of spare time on your hands.

"It works great locally" - Um, no it doesn't?

They've made a nice easy-to-use ecosystem. For $400 you can get a P1S that supports adding an AMS, auto bed leveling, enclosed-chamber printing, high precision, high print speeds, and 300/100C nozzle/plate temps, and has an easy cloud print service and a robust ecosystem of models you can just download and print with no extra config straight from the app.

But yeah, their behavior is increasingly entering bad-actor territory. I wonder how long it'll be before they lock entry-level printers into their branded filament?

Yes, but now you have it too complicated for 95% of the vibe coders. So they simply won't do it. Because skipping all of those steps still results in something that compiles.

They fuck up spreadsheets as well. A truckload of business-critical spreadsheets have errors in them that often go undetected for years.

It's hard enough to get actual developers to properly consider security. Not surprised at all that vibe coders don't.

Plus, of course, most of the training data is insecure to begin with.

But let them learn by fire that there's a reason actual programmers take time to ship a product, and it's not that the AI can type faster.

Boom meet bust.

Problem is: We don't even know what consciousness is.

So the best we can say is if something creates the impression of having one, based on whom we attribute consciousness to, i.e. other humans. Well, big surprise that a model explicitly trained on human language and texts creates that impression. It does show just how good the models are. At pretending to be human because they have a shitload of examples on what humans would say.

For all we know, the gas clouds on Jupiter could be conscious, just in a way that is completely baffling to us. We can't rule it out because we don't know what consciousness is, so we can't test for it.