I suspect that it wildly varies based on user.

If you use video streaming from, say, YouTube and TikTok heavily, and you do so outside of WiFi networks, I bet that you can burn through a lot of data pretty quickly.

Another user could be sitting on Lemmy or whatever all day every day and just not use much data.

@dumbass@lemmy.world @dumbass@sh.itjust.works @dumbass@sopuli.xyz

Lot of that going around, apparently.

https://en.wikipedia.org/wiki/Multi-user_dungeon

For a list of still-active MUDs:

https://www.mudconnect.com/

I think that the problem will be if software comes out that’s doesn’t target home PCs. That’s not impossible. I mean, that happens today with Web services. Closed-weight AI models aren’t going to be released to run on your home computer. I don’t use Office 365, but I understand that at least some of that is a cloud service.

Like, say the developer of Video Game X says “I don’t want to target a ton of different pieces of hardware. I want to tune for a single one. I don’t want to target multiple OSes. I’m tired of people pirating my software. I can reduce cheating. I’m just going to release for a single cloud platform.”

Nobody is going to take your hardware away. And you can probably keep running Linux or whatever. But…not all the new software you want to use may be something that you can run locally, if it isn’t released for your platform. Maybe you’ll use some kind of thin-client software — think telnet, ssh, RDP, VNC, etc for past iterations of this — to use that software remotely on your Thinkpad. But…can’t run it yourself.

If it happens, I think that that’s what you’d see. More and more software would just be available only to run remotely. Phones and PCs would still exist, but they’d increasingly run a thin client, not run software locally. Same way a lot of software migrated to web services that we use with a Web browser, but with a protocol and software more aimed at low-latency, high-bandwidth use. Nobody would ban existing local software, but a lot of it would stagnate. A lot of new and exciting stuff would only be available as an online service. More and more people would buy computers that are only really suitable for use as a thin client — fewer resources, closer to a smartphone than what we conventionally think of as a computer.

EDIT: I’d add that this is basically the scenario that the AGPL is aimed at dealing with. The concern was that people would just run open-source software as a service. They could build on that base, make their own improvements. They’d never release binaries to end users, so they wouldn’t hit the traditional GPL’s obligation to release source to anyone who gets the binary. The AGPL requires source distribution to people who even just use the software.

I will say that, realistically, in terms purely of physical distance, a lot of the world’s population is in a city and probably isn’t too far from a datacenter.

https://calculatorshub.net/computing/fiber-latency-calculator/

It’s about five microseconds of latency per kilometer down fiber optics. Ten microseconds for a round-trip.

I think a larger issue might be bandwidth for some applications. Like, if you want to unicast uncompressed video to every computer user, say, you’re going to need an ungodly amount of bandwidth.

DisplayPort looks like it’s currently up to 80Gb/sec. Okay, not everyone is currently saturating that, but if you want comparable capability, that’s what you’re going to have to be moving from a datacenter to every user. For video alone. And that’s assuming that they don’t have multiple monitors or something.

I can believe that it is cheaper to have many computers in a datacenter. I am not sold that any gains will more than offset the cost of the staggering fiber rollout that this would require.

EDIT: There are situations where it is completely reasonable to use (relatively) thin clients. That’s, well, what a lot of the Web is — browser thin clients accessing software running on remote computers. I’m typing this comment into Eternity before it gets sent to a Lemmy instance on a server in Oregon, much further away than the closest datacenter to me. That works fine.

But “do a lot of stuff in a browser” isn’t the same thing as “eliminate the PC entirely”.

“Write code without learning it!” I get it. I’ve struggled learning to program for 10 years. But every time I hear a programmer talk about AIGen code, it’s never good, and my job’s software has gotten less stable as AIGen code as been added in.

I’m similarly dubious about using LLMs to do code. I’m certainly not opposed to automation — software development has seen massive amounts of automation over the decades. But software is not very tolerant of errors.

If you’re using an LLM to generate text for human consumption, then an error here or there often isn’t a huge deal. We get cued by text; “approximately right” is often pretty good for the way we process language. Same thing with images. It’s why, say, an oil painting works; it’s not a perfect depiction of the world, but it’s enough to cue our brain.

There are situations where “approximately right” might be more-reasonable in software development. There are some where it might even be pretty good — instead of manually-writing commit messages, which are for human consumption, maybe we could have LLMs describe what code changes do, and as LLMs get better, the descriptions improve too.

This doesn’t mean that I think that AI and writing code can’t work. I’m sure that it’s possible to build an AGI that does fantastic things. I’m just not very impressed by using a straight LLM, and I think that the limitations are pretty fundamental.

I’m not completely willing to say that it’s impossible. Maybe we could develop, oh, some kind of very-strongly-typed programming language aimed specifically at this job, where LLMs are a good heuristic to come up with solutions, and the typing system is aimed at checking that work. That might not be possible, but right now, we’re trying to work with programming languages designed for humans.

Maybe LLMs will pave the way to getting systems in place that have computers do software engineering, and then later we can just slip in more-sophisticated AI.

But I don’t think that the current approach will wind up being the solution.

“Summarize a book!” I am doing this for fun, why would I want to?

Summarizing text — probably not primarily books — is one area that I think might be more useful. It is a task that many people do spend time doing. Maybe it’s combining multiple reports from subordinates, say, and then pushing a summary upwards.

“Generate any image!” I get the desire, but I can’t ignore the broader context of how we treat artists. Also the images don’t look that great anyway.

I think that in general, quality issues are not fundamental.

There are some things that we want to do that I don’t think that the the current approaches will do well, like producing consistent representations of characters. There are people working on it. Will they work? Maybe. I think that for, say, editorial illustration for a magazine, it can be a pretty decent tool today.

I’ve also been fairly impressed with voice synth done via genAI, though it’s one area that I haven’t dug into deeply.

I think that there’s a solid use case for voice query and response on smartphones. On a desktop, I can generally sit down and browse webpages, even if an LLM might combine information more quickly than I can manually. Someone, say, driving a car or walking somewhere can ask a question and have an LLM spit out an answer.

I think that image tagging can be a pretty useful case. It doesn’t have to be perfect — just be a lot cheaper and more universal than it would to have humans doing it.

Some of what we’re doing now, both on the part of implementers and on the R&D people working on the core technologies, is understanding what the fundamental roadblocks are, and quantifying strengths and weaknesses. That’s part of the process for anything you do. I can see an argument that more-limited resources should be put on implementation, but a company is going to have to go out and try something and then say “okay, this is what does and doesn’t work for us” in order to know what to require in the next iteration. And that’s not new. Take, oh, the Macintosh. Apple tried to put out the Lisa. It wasn’t a market success. But taking what did work and correcting what didn’t was a lot of what led to the Macintosh, which was a much larger success and closer to what the market wanted. It’s going to be an iterative process.

I also think that some of that is laying the groundwork for more-sophisticated AI systems to be dropped in. Like, if you think of, say, an LLM now as a placeholder for a more-sophisticated system down the line, the interfaces are being built into other software to make use of more-sophisticated systems. You just change out the backend. So some of that is going to be positioning not just for the current crop, but tomorrow’s crop of systems.

If you remember the Web around the late 1990s, the companies that did have websites were often pretty amateurish-looking. They were often not very useful. The teams that made them didn’t have a lot of resources. The tools to work with websites were still limited, and best practices not developed.

https://www.webdesignmuseum.org/gallery/year-1997

But what they did was get a website up, start people using them, and start building the infrastructure for what, some years later, was a much-more-important part of the company’s interface and operations.

I think that that’s where we are now regarding use of AI. Some people are doing things that won’t wind up ultimately working (e.g. the way Web portals never really took over, for the Web). Some important things, like widespread encryption, weren’t yet deployed. The languages and toolkits for doing development didn’t really yet exist. Stuff like Web search, which today is a lot more approachable and something that we simply consider pretty fundamental to use of the Web, wasn’t all that great. If you looked at the Web in 1997, it had a lot of deficiencies compared to brick-and-mortar companies. But…that also wasn’t where things stayed.

Today, we’re making dramatic changes to how models work, like the rise of MoEs. I don’t think that there’s much of a consensus on what hardware we’ll wind up using. Training is computationally expensive. Just using models on a computer yourself still involves a fair amount of technical knowledge, the sort of way the MS-DOS era on personal computers prevented a lot of people from being able to do a lot with computers. There are efficiency issues, and basic techniques for doing things like condensing knowledge are still being developed. LLMs people are building today have very little “mutable” memory — you’re taking a snapshot of information at training time and making something that can do very little learning at runtime. But if I had to make a guess, a lot of those things will be worked out.

I am pretty bullish on AI in the long term. I think that we’re going to figure out general intelligence, and make things that can increasingly do human-level things. I don’t think that that’s going to be a hundred years in the future. I think that it’ll be sooner.

But I don’t know whether any one company doing something today is going to be a massive success, especially in the next, say, five years. I don’t know whether we will fundamentally change some of the approaches we used. We worked on self-driving cars for a long time. I remember watching video of early self-driving cars in the mid-1980s. It’s 2026 now. That was a long time. I can get in a robotaxi and be taken down the freeway and around my metro area. It’s still not a complete drop-in replacement for human drivers. But we’re getting pretty close to being able to use the things in most of the same ways that we do human drivers. If you’d have asked me in 2000 whether we would make self-driving cars, I would say basically what I do about advanced AI today — I’m quite bullish on the long-term outcome, but I couldn’t tell you exactly when it’ll happen. And I think that that advanced AI will be extremely impactful.

You could also just only use Macs.

I actually don’t know what the current requirement is. Back in the day, Apple used to build some of the OS — like QuickDraw — into the ROMs, so unless you had a physical Mac, not just a purchased copy of MacOS, you couldn’t legally run MacOS, since the ROM contents were copyrighted, and doing so would require infringing on the ROM copyright. Apple obviously doesn’t care about this most of the time, but I imagine that if it becomes institutionalized at places that make real money, they might.

But I don’t know if that’s still the case today. I’m vaguely recalling that there was some period where part of Apple’s EULA for MacOS prohibited running MacOS on non-Apple hardware, which would have been a different method of trying to tie it to the hardware.

searches

This is from 2019, and it sounds like at that point, Apple was leveraging the EULAs.

https://discussions.apple.com/thread/250646417?sortBy=rank

Posted on Sep 20, 2019 5:05 AM

The widely held consensus is that it is only legal to run virtual copies of macOS on a genuine Apple made Apple Mac computer.

There are numerous packages to do this but as above they all have to be done on a genuine Apple Mac.

• VMware Fusion - this allows creating VMs that run as windows within a normal Mac environment. You can therefore have a virtual Mac running inside a Mac. This is useful to either run simultaneously different versions of macOS or to run a test environment inside your production environment. A lot of people are going to use this approach to run an older version of macOS which supports 32bit apps as macOS Catalina will not support old 32bit apps.
• VMware ESXi aka vSphere - this is a different approach known as a ‘bare metal’ approach. With this you use a special VMware environment and then inside that create and run virtual machines. So on a Mac you could create one or more virtual Mac but these would run inside ESXi and not inside a Mac environment. It is more commonly used in enterprise situations and hence less applicable to Mac users.
• Parallels Desktop - this works in the same way as VMware Fusion but is written by Parallels instead.
• VirtualBox - this works in the same way as VMware Fusion and Parallels Desktop. Unlike those it is free of charge. Ostensible it is ‘owned’ by Oracle. It works but at least with regards to running virtual copies of macOS is still vastly inferior to VMware Fusion and Parallels Desktop. (You get what you pay for.)

Last time I checked Apple’s terms you could do the following.

• Run a virtualised copy of macOS on a genuine Apple made Mac for the purposes of doing software development
• Run a virtualised copy of macOS on a genuine Apple made Mac for the purposes of testing
• Run a virtualised copy of macOS on a genuine Apple made Mac for the purposes of being a server
• Run a virtualised copy of macOS on a genuine Apple made Mac for personal non-commercial use

No. Apple spells this out very clearly in the License Agreement for macOS. Must be installed on Apple branded hardware.

They switched to ARM in 2020, so unless their legal position changed around ARM, I’d guess that they’re probably still relying on the EULA restrictions. That being said, EULAs have also been thrown out for various reasons, so…shrugs

goes looking for the actual license text.

Yeah, this is Tahoe’s EULA, the most-recent release:

https://www.apple.com/legal/sla/docs/macOSTahoe.pdf

Page 2 (of 895 pages):

They allow only on Apple-branded hardware for individual purchases unless you buy from the Mac Store. For Mac Store purchases, they allow up to two virtual instances of MacOS to be executed on Apple-branded hardware that is also running the OS, and only under certain conditions (like for software development). And for volume purchase contracts, they say that the terms are whatever the purchaser negotiated. I’m assuming that there’s no chance that Apple is going to grant some “go use it as much as you want whenever you want to do CI tests or builds for open-source projects targeting MacOS” license.

So for the general case, the EULA prohibits you from running MacOS wherever on non-Apple hardware.

Now my question is, who’s making that one query that leaks my domain name? Is it Apache on startup

If you’re wanting a list of DNS queries from your system, assuming that it’s DNS and not DoH, maybe:

# tcpdump port domain

Then go start Apache or whatever.

Okay, this is unfortunately DIY, but if you’re willing to spend time:

Get a plywood box and put it in there.

If you hear vibrations, put sorbothane between the NAS and the box.

If you need more sound absorption, put acoustic foam on the inside.

If you need more cooling, drill two holes, mount a case fan, and run the air through some kind of baffle. Like, maybe attach insulated flex-duct, like this:

https://www.amazon.com/Hon-Guan-Silencer-Reducer-Ventilation/dp/B07HC8CXQG

I wonder if problems could be mostly avoided by running potentially-unsafe code in a container without network access.

Yes. For a single change. Like having an editor with 2 minute save lag, pushing commit using program running on cassette tapes4 or playing chess over snail-mail. It’s 2026 for Pete’s sake, and we5 won’t tolerate this behavior!

Now of course, in some Perfect World, GitHub could have a local runner with all the bells and whistles. Or maybe something that would allow me to quickly check for progress upon the push6 or even something like a “scratch commit”, i.e. a way that I could testbed different runs without polluting history of both Git and Action runs.

For the love of all that is holy, don’t let GitHub Actions manage your logic. Keep your scripts under your own damn control and just make the Actions call them!

I don’t use GitHub Actions and am not familiar with it, but if you’re using it for continuous integration or build stuff, I’d think that it’s probably a good idea to have that decoupled from GitHub anyway, unless you want to be unable to do development without an Internet connection and access to GitHub.

I mean, I’d wager that someone out there has already built some kind of system to do this for git projects. If you need some kind of isolated, reproducible environment, maybe Podman or similar, and just have some framework to run it?

like macOS builds that would be quite hard to get otherwise

Does Rust not do cross-compilation?

searches

It looks like it can.

https://rust-lang.github.io/rustup/cross-compilation.html

I guess maybe MacOS CI might be a pain to do locally on a non-MacOS machine. You can’t just freely redistribute MacOS.

goes looking

Maybe this?

https://www.darlinghq.org/

Darling is a translation layer that lets you run macOS software on Linux

That sounds a lot like Wine

And it is! Wine lets you run Windows software on Linux, and Darling does the same for macOS software.

As long as that’s sufficient, I’d think that you could maybe run MacOS CI in Darling in Podman? Podman can run on Linux, MacOS, Windows, and BSD, and if you can run Darling in Podman, I’d think that you’d be able to run MacOS stuff on whatever.

I think that it’s going to be hard to provide a meaningful answer. There are a wide range of fields that use the scientific process, the stuff that you’d call “science”.

Some of those, no doubt, produce a strong return on investment. You could say, purely on finnacial terms, that research there makes a lot of sense. Producing, say, the integrated circuit is something that transformed the world.

I am sure that if you looked, you could find some areas that don’t do that.

In some of these latter cases — say, cosmology — I doubt that there are likely direct financial returns, but if we want to understand where the universe has been and where it’s going, we have to place some kind of value on that and fund it to that value.

But…science isn’t a single entity that you fund or don’t fund to a given amount. It’s people working in a wide range of fields. It’s like saying “should we fund sysadmins more” or “should we fund human resource departments more”. The answer is almost certainly going to be “it depends on the specific case”.

I tried a fully fledged consumer NAS (QNAP with Seagate 12 TB NAS drives) but the noise of the platters was not acceptable.

If you have a NAS, then you can put it as far away as your network reaches. Just put it somewhere where you can’t hear the thing.

I think that Starlink covers a lot of disaster scenarios.

More AI datacenters being planned.

“I think we’ve done a lot of damage with very well-respected people who have painted a doomer narrative, end of the world narrative, science fiction narrative,” Huang said.

I mean, part of the role of science fiction is to try to look at the future as technology changes it. Not all of it is hard sci-fi, but I wouldn’t across-the-board discount sci-fi. A lot of changes have been in sci-fi before reality.

There are some products out there that do cater to people who want a physical keyboard on their smartphone today. It’s not the norm, but if you’re frustrated over it, it might work for you.

Amazon has a lot of portable Bluetooth keyboards that can basically collapse down into a pocket. Those are generally designed to be used at a table, though, not in a Blackberry-style thumb keyboard sense. I’m pretty sure that I’ve seen a few of the latter that can clip to a phone, though.

while visiting family in LA I saw a robot waiter which both (optionally) took orders and would serve as a mobile food/plate tray.

Yeah, I’ve run into these. That being said, I’d call them currently a novelty…but I also remember when using touchscreen kiosks for ordering instead of cashiers was a rarity.

There was some similar project that the UK was going to do, run an HVDC submarine line down from the UK to Africa.

searches

https://en.wikipedia.org/wiki/Xlinks_Morocco–UK_Power_Project

The Xlinks Morocco-UK Power Project is a proposal to create 11.5 GW of renewable generation, 22.5 GWh of battery storage and a 3.6 GW high-voltage direct current interconnector to carry solar and wind-generated electricity from Morocco to the United Kingdom.[1][2][3][4] Morocco has been hailed as a potential key power generator for Europe as the continent looks to reduce reliance on fossil fuels.[5]

If built, the 4,000 km (2,500 miles) cable would be the world’s longest undersea power cable, and would supply up to 8% of the UK’s electricity consumption.[6][7][8] The project was projected to be operational within a decade.[9][10] The proposal was rejected by the UK government in June 2025.