Users should never be able to do things that cause crashes in the same way that drivers should not ever be able to press any button or press any pedal that causes the engine to spontaneously burst into flames.

I'm also a Mac user, but let's not boast here, shall we?

My personal guess would have been at least 10x. Did Microsoft bribe the study authors?

Dude, are you living under a rock?

These bands are creating new music. But the money that allows them to do so comes from their old music. I have bands in my collection that have been making music for 30 years.

No they don't. They don't even make ok money. Tours are expensive and a lot of people, from road crew to venue security, take their cut before the musicians. The big guys, they make a killing on tours. But the small ones sometimes don't even break even.

In fact, a common wisdom in the industry is that touring is worth it not because the tour itself makes profits, but because it builds a fanbase and drives what is called "catalog discovery" - both old and new fans looking buying the albums with the songs they liked (and for the old fans, didn't know).

This study: https://www.giarts.org/article... says that 28% of income across all the musicians surveyed comes from tours. The share is larger for the rock/pop sector where it nears 40% but even that isn't easy money. And if you consider that only 20% of the rock/pop musicians make more than $50,000 a year, then it becomes a hollow statement.

Plus, it goes directly against your first statement - while on tour the band is not creating new music. So if you want to drive musicians more towards constantly creating (which most of them already do), then you can't make live performances the main income source.

The public/private key can be big and slow, as it's only used during the initial handshaking and login anyway. I'm not going to notice any extra couple if tenths of a second logging in.

After that everything is (much much faster) symmetric encryption.

You still need a PQC algorithm here too, though. AES-256 is still considered quantum-resistant, for now, at least, so we're good.

Just reading that - "ChatGPT's Erotic Mode" - felt slimy and gross.

There is more than one study and more than one way to look at it. Especially for streaming, having a catalog matters, especially for the smaller artists who will never have a charts-level hit:

"In 2024, nearly 1,500 artists generated over $1 million in royalties from Spotify aloneâ"likely translating to over $4 million across all recorded revenue sources. What's remarkable is that 80% of these million-dollar earners didn't have a single song reach the Spotify Global Daily Top 50 chart. This reveals a fundamental shift from hit-driven success to sustainable catalog-based income, where consistent engagement from devoted audiences matters more than viral moments or radio dominance."

https://cord-cutters.gadgethac...

Also don't forget that many studies such as DiCola's "Money from Music" focus on the superstars and the big hits. That is true, the charts pop music generates 80% or so of its income within the few weeks it stays in the charts and then drops of sharply.

Honestly, I don't care about the charts and superstars. They wouldn't starve if we cut copyright terms to six weeks. I do care about the indie artists that I enjoy. Who after ten years get the band back together for another tour through clubs with 200 or 500 people capacity. I'm fairly sure they would suffer if the revenue from those albums disappeared. And disappear it would. Maybe fans would still buy the CDs from the merch booth, but Spotify would certainly not pay them if it didn't have to.

This is another 404 Media pay-for-placement post here on Slashdot. They're pretty much all low-quality hide-your-blogpost-behind-a-paywall drivel.

In order to get numbers like 5 million gallons one has to be looking at the very largest data centers, counting all water use as single use, even though water used for cooling is often reusable, and counting all the water used not by the center directly but used for power plants also as discussed earlier. Typical data center consumption is much lower. For example, see https://www.brookings.edu/articles/ai-data-centers-and-water/ which has one of the high-end estimates for what a typical data center consumes. As for the idea that there's a lot of data centers being built in the Southwest, more are being built or planned to be built in California or on the East Coast. Northern Virgina is the fastest growing region for data centers. See map here https://usdatamap.com/ (This isn't a perfect map. The situation is in flux. And admittedly, this map doesn't show size of them. My impression is that at least some of the ones being built in Arizona are very large so the map here isn't showing everything.)

Yes, building some of the largest data centers, making them all near one city, would take up a lot of water. However, that would be silly; the people building these are not idiots and aren't going to go shove all their centers in a region they know they then won't have enough water for all of them. Moreover, in many jurisdictions, one has historical water rights to contend with. In many jurisdictions for major water resources, historical users get priority over new users, so farmers and others would get priority before data centers if it came down to that. (Yes, this does mean that in parts of California, golf courses get priority over some other uses.)

This is not remotely why AI systems are being used. ChatGPT is being used daily by hundreds of millions of people https://explodingtopics.com/blog/chatgpt-users. Right now, ChatGPT is the 5th most visited website in the world by some independent metrics. https://en.wikipedia.org/wiki/List_of_most-visited_websites. These systems are not being used just because some rich people want to not have to pay people or bother with civility. The regular, common people are using them. Understanding where this is going, the impacts it will have, both positive and negative, requires understanding the actual usage, not what one imagines it to be.

The water use for AI seems to be greatly exaggerated. Estimating water use complicated. Different data centers use different amounts of water. Also, systems need more water use for cooling when the weather is hot, so centers may use more water in summer. A data center will use more water when the center is at close to maximum usage, so data centers will use less water if they are handling queries when few users are using the system. Complicating things even further, some people are counting not just data cooling water but also counting the indirect water use from the needed electricity production (fossil fuel and nuclear plants use a fair bit of water for their steam turbines). There's a good article here discussing the difficulties in making water estimates https://theconversation.com/ai-has-a-hidden-water-cost-heres-how-to-calculate-yours-263252 However, all things considered. they estimate that all things considered it takes about 39 milliliters of water per a typical query. Now, for comparison, a high efficiency shower uses about 1.5 gallons of water a minute, which is about 95 ml of water a second. So making a query to an LLM AI system costs less than a second of water. If this estimate is off even by a factor of 3, this is equivalent to taking 1 second longer on a shower. The water use is just not hat high. The total water use is also not very high. If for example you use estimates for how much water is used by golf courses in the US https://www.usga.org/content/dam/usga/pdf/Water%20Resource%20Center/how-much-water-does-golf-use.pdf, the largest estimates of AI use put the water use as about a tenth of the water use by golf courses, and golf course water estimates put it at most about 1% of total US water use. So even if one is concerned, just getting rid of some of the gigantic water hungry golf courses in California and Arizona (seriously who the heck puts a golf course in Arizona) would largely offset this. Now, it is true that as data centers grow, more water will likely get used. But as we switch to more wind and solar power, the indirect water use will go down, and data center builders are working hard on reducing water use since it is such a hotbutton issue.

There are a lot of legitimate concerns about AI. Water use should not be high on the list.

I think one of the problems Asahi runs into is that macOS can already be used for almost everything a Linux box can be used for - so it's harder to get excited about working on it.

My work-provided laptop is an M3 MacBook Air. I use it to admin ~ 100 Linux servers and workstations, and I can't say I've yet run into a situation where I said "darn it, that apparently doesn't work on a Mac". There are some command-line switches that are different between the two, but I think that mostly comes down to the difference between BSD vs. Mac. And I can (and do) install the Gnu tools.

Reddit only posted a profit when they started to sell all of their users comments to AI companies. Those companies don't want to pay to recycle their own AI comments back into their AI, so Reddit needs help to make sure as much of the comments aren't bots.

These issues are all very minor. Submarines are cramped and people can remain incommunicado for months. Messages to Earth is essentially just means one will be relying on email equivalent. And vacuum packed food can keep for years. Drinking water that is reclaimed from pee isn't fun, but isn't a big deal.

Mechanical problems are a big issue. That's why for example even today submarines carry some replacement parts, and why big surface ships historically had machine shops. Some things will need to be carried. But others may need to be ready to be made on site. That's why there's now a 3D printer on the ISS, to get used to doing exactly this. The gravity issue isn't a large one: on a 90 to 120 day mission to Mars, the level of bodily deteriorating isn't that big. We don't have a lot of data for the exact "how bad is it" but I'd strongly suspect that 3 days in microgravity and then 2 years on the Moon is going to be much worse than 90 days in microgravity and then 2 years on Mars.

A 90 or 120 day trip just isn't that big an issue. People have spent far longer on the ISS and managed fine.

People don't go insane and murder each other nearly as much as they do in movies. Again, look at submarines. The degree to which there are psychological issues is drastically exaggerated.

One of the lessons from the ISS and Mir is how incredibly difficult and expensive in-orbit construction is. Now, we've learned from it but its still a big issue. If you want to send 12 people then the most pessimistic estimates give you around 250 tons of stuff for a 2 year mission. That's only slightly higher than the Starship design, which is capable of being built on Earth, and masses about 5000 tons. Serious on Earth-designs for rockets have been bigger than that. For example Sea Dragon was going to mass 18,000 tons. And you can also do things to reduce the difficulty by launching multiple rockets, say one with the humans and the stuff they need for the first few months, and then another just full of cargo.

AI systems are useful to many people. Most users aren't getting it as an investment engine itself. They are using them to do things like assist with programming, look over drafts of documents, do specific searches and other things. Don't mistake valuable to you personally as the sole form of relevant value.

He's basically a newborn :-)

Yes, but there is an important difference: TV had to appeal to an average audience member. Meanwhile the social media algorithms are intentionally working against you, trying to specifically find and use your triggers.

That's quite a different intent there.

On the TV, parents could also check the program for what they thought was suitable for their kid or not. They could watch the same program, even if not in the same room. Social media is a lot more personal and a lot harder to track and filter.