Perhaps, but I suspect Starlink (etc) already fills most of that use-case, and for the rest, they'll want that compute to be physically located inside the drones themselves, because otherwise the drones will be susceptible to jamming or spoofing.

There will be jobs that AI can't do. How many? Enough to keep 5-10 billion humans employed? What makes you so sure there will be?

Clearly AI has progressed considerably over the last 5-10 years. It's anyone's guess how much further it will progress -- maybe it'll plateau right where it is now, or maybe it will keep becoming more powerful as better algorithms are discovered. I'm not qualified to predict that, and neither are you, but the AI people certainly seem bullish about it.

Sorry, I thought you would understand that I meant that the resources that money represents appear, once you've solved the automation problems that currently make mass-production difficult. That's why you can buy a pocket computer today for $300 that would have your cost you billions of dollars twenty years ago, if you could have obtained it at all.

I bet you'd have more interesting conversations if you made a good-faith effort to understand what the other person was saying, rather than just jumping straight to the part where you get to throw insults at them and tell them how dumb they are. Doesn't that get boring?

I have yet to hear of a remotely plausible business case for putting data centers into space. The only benefit is 24/7 solar power, but that benefit is more than offset by the cost of launching everything into orbit, plus the cost of keeping everything properly cooled, plus the cost of radiation-hardening everything, and finally the cost of maintaining hardware in space (or, more likely, the cost of periodically having to write off the entire investment and build and launch new replacement hardware).

Unless Musk is trying to corner the market for AI-generated kiddie-porn (or something similarly illegal that needs to be operated beyond the reach of Earthly authorities), his ground-based competitors will undercut his pricing by a factor of 100, and he therefore won't have a viable product to sell.

Certainly new categories of work will emerge. The question is, will hiring and paying human beings be the most economically efficient way to fill those new positions, or will those jobs be done by AIs instead?

Previous waves of automation allowed people to move "up the food chain" and do jobs the machines still couldn't do, which was fine (at least, for the people capable of doing the new jobs), but if we get to the stage where there aren't many jobs left that the machines can't do, then we're out of luck -- it's unlikely that our tech-bro overlords are going to hire people simply on humanitarian grounds, if they can get an unquestioning machine to do the same work cheaper.

I agree that UBI is unlikely, but only because the billionaires don't like sharing and therefore won't support it. The money does "just appear" when you have mass automation doing the work to make it appear, but it will go into Bezos' checking account, not to the general public.

Yes, and that's the problem for Disney -- theme parks can only physically accept so many people per year, and they can't (easily) build more of them. So theme parks can't be more than a small amount of their total income; to really make the big money, the Mouse has to ship products that can and will be purchased by everyone. In practice, that means movies; ideally good movies, but at a minimum, popular movies.

Maybe, but the problem is that the electronics have to run at those temperatures and not have solder joints start popping, or other fun failures.

As far as I know, it is just real-time. And it didn't even slow down at the flashing red light. So either it recognized that someone was waving it on or it didn't see the flashing light at all.

I *think* that number actually is counting them, though it's hard to be certain. I'm pretty sure servers are outnumbered by PCs by a large margin.

Cameras and LIDAR. I am not a self-driving car engineer, but from what I understand, it seems likely that it is possible to detect water with even just cameras, at least under the right circumstances, and with cameras plus LIDAR under a lot more circumstances. But doing so would require proper training data; it's not like there's a "Ooh, that's water" recognizer built into the hardware or whatever.

More to the point, they would have to train it how to recognize that some particular sensor return pattern (e.g. zero LIDAR reflections off the ground) is a problem, and do so in a way that doesn't over-correct for flooded potholes, an inch of water in the street, etc. Presumably, detecting water is the easy part; detecting the depth of water is the hard part unless you know exactly how high the curbs are.

I'm a little spooked when I see Tesla FSD beta demos where the car plows right on ahead through slightly flooded streets as though there's nothing there. It makes me wonder whether it saw it and ignored it or just didn't see it. It's the same feeling I got this morning when someone was signaling me to go ahead at a flashing red light and FSD beta (12.6.4) went right on ahead. I wonder if it somehow saw the hand gestures, or if it just didn't see the flashing red light at all.

That's what makes all this stuff fun.

Any hardware or device driver engineer will tell you that every hardware problem, once shipped, is a software problem. :-) (Translation: Hardware bugs, once the hardware is in the wild, have to be fixed with a software workaround.)

Nothing in self-driving cars is a quick fix other than geo-blocking something. You have to train a visual or LIDAR recognition model to recognize the problem situation and then train the path finding model to flag it as a bad path. How hard that is for this particular case, I have no idea. And there's probably other stuff beyond that; I'm not an expert in this area.

Yeah, there's not enough crack in the world for that to make sense. The cost-to-orbit is well documented. Artemis 2: $4.1 billion for a launch that can lift 95 tons to LEO. SuperHeavy/Starship: $90 million for a launch that can lift 150 tons to LEO. Ignoring minor details (e.g. that nobody is willing to expend a SuperHeavy to do trans-lunar injection), the reality of the matter is that the cost per ton to orbit for NASA rockets is 72x what it is expected to cost for SpaceX rockets.

And that's consistent with Falcon Heavy costs, too, so you can't hide behind "Yeah, but SuperHeavy and Starship don't work yet", because unless your payload is huge, SpaceX is still almost two orders of magnitude cheaper.

That never made much sense to me. The power requirements and cooling requirements for a data center in the vacuum of space would be completely infeasible.

The most any commercial satellite has ever dissipated, as far as I know, is only low-double-digit kilowatts worth of heat. Three high-end NVIDIA AI cards per satellite would basically fully max out a typical satellite's heat dissipation, without factoring in any of the heat produced from communication hardware, energy storage, solar heating, or heat dissipation from the computer that's powering those GPUs.

A large data center would likely include one or more clusters of 100,000 GPUs, not three. A typical communications satellite is on the order of 220 square meters. Do the math, and you get 7,333,260 square meters, or 7.3 square km. This translates to a radius of .76 km, or a diameter of 1.52 km. Sure, it might not be not as dense as a meteor of that diameter, but it would still be really, really bad to deorbit something that size. I would not be surprised if the resulting dust cloud causes crop failures for years on a scale that would wipe out a sizable percentage of human life.

If, by data center, you just mean an edge cache like Cloudflare or Akamai, then it might be slightly more feasible, but even that is pushing the limits of my suspension of disbelief.

Why would you take macOS out? It's a full UNIX environment, complete with a command line.

Agreed.

What made Linux the most widely used and successful OS was Android. But Linux and *BSD have fairly similar numbers of installations. You have 2.5 billion Apple devices (mac, iOS, etc.) versus 4 billion Android devices, you have more iOT devices on Linux, but a LOT more commercial routers and switches and other hardware on *BSD. It's really hard to calculate, but the numbers are probably within +/- 20% of being the same.

The problem is, none of those devices really qualify as Linux in any meaningful sense. Sure, they run the kernel, but that's about it. The user-space tools that GPL had such a big influence on are not there at all. Take all the iOT devices and Android devices and Chromebooks out of the picture, and Linux ends up actually being less popular than *BSD (because of macOS).

So whether Linux is or is not the most widely used OS depends on how you measure it.

I don't see any real evidence for what you're saying. Linux succeeded more because it had better support for PC graphics hardware early on, and the *BSDs didn't get a chance to really catch up. And the AT&T-Berkeley lawsuit stalled BSD development and adoption during the early 90s as well. And the *BSDs were fragmented into multiple camps (386BSD forked into FreeBSD and NetBSD, and then NetBSD further forked into OpenBSD), while the only forking on the Linux side was over distros. The lack of a strong, central leader likely made a far bigger difference than anything else.

All of these things led to Linux having more people working on it early on, and ultimately, the group with the most developers wins. Maybe GPL got them slightly more developers, or maybe it didn't. There's really no way to know. But my guess is that for every extra developer who joined because of the GPL, there were two corporate developers who didn't join because of the GPL, so I highly doubt you are correct in your assessment.

At best, GPL made it harder (but not impossible) for hardware developers to ship closed-source drivers, which made it easier to keep supporting old hardware, which probably resulted in a slight increase in the thickness of the long tail of the user base. Whether this is a meaningful benefit or not is unclear, because it also comes with the extra overhead of continuing to support that long tail. :-)

No, statutory damages are per work. The minimum is $200 if the violator could show reasonable cause to have believed that the infringement was fair use, and the maximum is $150,000 in cases of willful infringement. The nominal range is $750 to $30,000.

To receive more than that requires showing actual damages. What this means is that even if there are a hundred GPLed projects whose licenses are being violated, short of proving willful infringement, apart from in injunction against further violations, the most they would likely get without showing actual damages is $3 million dollars, which is a slap on the wrist. And it's unclear how to show actual damages for something that you give away for free.

You *might* be able to make the claim that each new product line is a new infringement, but that's about the limit to what is realistic.