So, first, it’s trivial to make a wiki that aims to be an encyclopedia with some other viewpoint. Conservapedia is an (in)famous example.

The problem is that scale is very important to Wikipedia’s utility. It’s not the existence of the thing, but enough people who want to put useful information in it to make the thing valuable. If what you want is something comparable in utility to Wikipedia, that’s going to be a lot harder. You’re going to have to line up a lot of people who specifically want to write for that wiki, unless you can figure out some way to generate the thing outside of using human writers.

Second, I’d say that it’s hard to define Wikipedia as specifically American by many metrics that I’d consider important — I mean, content comes from people all over. My guess is that the great majority of content in, say, Georgian language Wikipedia is very probably not written by Americans. Might be that most English-language content is, though. shrugs

Wikipedia’s content is under a Creative Commons license, as I recall, so anyone can fork it, if you just want to host your own; the Wikimedia people put up the content in compressed form periodically. The MediaWiki software is open source, and you go go run your own instance of the stuff. I’ve seen various wikis that have basically just copied Wikipedia content and run it on their own MediaWiki instance.

https://en.wikipedia.org/wiki/List_of_content_forks_of_Wikipedia

https://en.wikipedia.org/wiki/List_of_online_encyclopedias

I’m going to be honest with you, though — I think that it’s going to be very hard to produce something that is really competitive with Wikipedia at an international level unless:

• You’re a state that just bans Wikipedia period and have major scale and maybe a predominant number of users in the language in question. Wikipedia says that China has blocked Wikipedia since April 23, 2019, for example.

  https://en.wikipedia.org/wiki/List_of_websites_blocked_in_mainland_China

  https://en.wikipedia.org/wiki/Baidu_Baike

  Baidu Baike (/ˈbaɪduː ˈbaɪkə/; Chinese: 百度百科; pinyin: Bǎidù Bǎikē; lit. ‘Baidu Encyclopedia’, also known as BaiduWiki internationally[1]) is a semi-regulated Chinese-language collaborative online encyclopedia owned by the Chinese technology company Baidu.[2] Modelled after Wikipedia, it was launched in April 2006.[3] As of 2025, it claims more than 30 million entries[4] and around 8.03 million editors [5]— the largest number of entries of any Chinese-language online encyclopedia.[6] Baidu Baike has been criticised for its censorship, copyright violations, commercialist practices and unsourced or inaccurate information.[7][8][9][10]

• You are going to do basically the same thing, but with a coalition of states. I’m skeptical that there are a lot of coalitions that have similar language and similar content concerns, but…oh, for example, there are a number of Muslim states who don’t like their citizens having access to LGBT stuff. That’s come up on here, where users of some Threadiverse instances — e.g. the transexual-oriented lemmy.blahaj.zone — are blocked from those countries. Maybe someone could get many states to do something like a “Muslim-acceptable Standard Arabic encyclopedia” or something, and block competitors. A big problem here is that I suspect that a lot of those states also have problems with narratives that other countries have. For example, Morocco and Algeria probably are not going to be happy about articles relating to the Western Sahara. Maybe you could make an encyclopedia that specifically facilitates political censorship on particular topics, like “this article has been flagged as one where there is a Morocco and Algeria version, and you can only see your version in your country”. That wouldn’t be very appealing to me, but I could imagine making something like that work.

• You do one of the above two options, but instead of an alternative to Wikipedia, you maintain an actively-merged fork that keeps merging from upstream Wikipedia. Like, say you’re fine with Wikipedia in general, don’t have a problem with, say, policy or citing or whatever, but you are super-upset about content relating to a relatively-small portion of the wiki. I think that this is true of very many people who don’t like Wikipedia for one reason or another. Like, they don’t care about, say, Wikipedia’s article on furniture, but they really get upset about articles that relate to religion or politics or whatever in some area where they don’t agree. So, you write software that is set up to maintain an “active fork”. Like, each page has something like a patch to yank out content that you don’t like, which gets re-applied whenever the Wikipedia version of the page is updated. This sort of thing is not uncommon in software development, working with source code rather than human language text. If a merge fails on a new version of a page, then you just keep the old version of the page until a human can go update the patch, which is an option that isn’t really available with software development. Some of the pages will get out of date, and there’s going to be an ongoing labor cost, and you always are going to have some amount of content that you don’t like leaking in, but it might be a lot less labor than doing a new encyclopedia.

• You use a radically-technically-different approach. Elon Musk, for example, has gone for an “alternative source of truth generated by an AI” with Grokipedia. I think that making that work is going to require a lot more technical work, but maybe down the line, if Musk can make it work, other states and institutions will also create their own alternative sources of truth generated by AIs.

  https://en.wikipedia.org/wiki/Grokipedia

  Grokipedia is an AI-generated online encyclopedia operated by the American company xAI. The site was launched on October 27, 2025. Some entries are generated by Grok, a large language model owned by the same company, while others were forked from Wikipedia, with some altered and some copied nearly verbatim. Articles cannot be directly edited, though logged-in visitors to the encyclopedia can suggest corrections via a pop-up form, which are reviewed by Grok.

  xAI founder Elon Musk positioned Grokipedia as an alternative to Wikipedia that would “purge out the propaganda” he believes is promoted by the latter,[1] with Musk describing Wikipedia as “woke” and an “extension of legacy media propaganda”.[2]

  My own personal suspicion is that the state of AI is not really sufficient to do a good job of this in early 2026. But I also suspect that it will eventually be — there are obviously people and institutions who want to have alternate sources of truth, either for themselves or because they don’t want other people exposed to Wikipedia for whatever reason, and AI might be one way of doing mass generation of content while baking in whatever political or ideological views one wants via use of software.

And here’s a thing about me. I want to trust new websites. I have a bias towards clicking on articles from sites I don’t know, because to be quite honest, I’ve read the TCRF page on Phantasy Star a thousand times. How else do you learn something new?

To some extent, I think that this is a solveable problem in terms of just weighting domain age and reputation more highly in search engines (and maybe in LLM training stuff).

The problem is that then you wind up with a situation where it’s hard for new media sources to compete with established incumbents, because the incumbents have all that reputation and new entrants have to build theirs, and new entrants get deprioritized by search engines.

I think that maybe there’s an argument that you could also provide a couple of user-configurable parameters on search engines to permit not deprioritizing newer sites and the like.

Another issue is that reputation can be bought and sold. This is not new. For example, you can buy a reputatable, established news source and then change its content to be less reputable but promote a message that you want. That will, over time, burn its credibility, but as long as the return you get is worth what you’ve spent…shrugs

Gotcha. I don’t use non-Threadiverse stuff myself, but if you do use communities like that, you might also be interested in retrolemmy.com:

https://retrolemmy.com/communities?listingType=Local&sort=TopMonth&page=1

I’m assuming that you aren’t wanting Threadiverse-based stuff like !retrogaming@lemmy.world?

I don’t know about stopping it if someone is sufficiently determined to get in, but if it’s a repeated problem, I suppose that you could put something that looks interesting to steal in the car with an AirTag-type tracking device or similar hidden in it and then provide the police with the thief’s track if they bite.

Putting visible cameras all over might deter some people.

I’d guess that parking in a garage would help, but you say elsewhere that that wasn’t an option here.

I want to clean my PC thoroughly to buy it a few more years.

Is it not working in its present state?

If it’s working all right, I’d just leave it be, and if you don’t want tar buildup in your next case, get a case that has an air filter on it that you can replace, or run an air purifier with a filter in the room.

Thanks, but was an error on my part; was trying to list stuff that didn’t have a sequel or remake. Hadn’t ever heard of them, but apparently there were two Indian film remakes and a television remake:

https://en.wikipedia.org/wiki/12_Angry_Men_(1957_film)

The 1986 Hindi film Ek Ruka Hua Faisla (“a pending decision”) and 2012 Kannada film Dashamukha (“ten faces”) are Indian remakes of the film, with almost identical storylines. The former has been adapted as another Indian Bengali film Shotyi Bole Shotyi Kichhu Nei which was released in January 2025.[71]

In 1997, a television remake of the film under the same title was directed by William Friedkin and produced by Metro-Goldwyn-Mayer. In the newer version, the judge is a woman, four of the jurors are black, and the ninth juror is not the only senior citizen, but the overall plot remains intact. Modernizations include not smoking in the jury room, changes in references to pop culture and sports figures and income, references to execution by lethal injection as opposed to the electric chair, more race-related dialogue, and casual profanity.

I mean, there are plenty of highly-rated movies that don’t have a sequel (and probably that’s a good thing).

• The Shawshank Redemption

• 12 Angry Men

• Schindler’s List

• Pulp Fiction

• Fight Club

If I’m traveling or I wipe my device or get a new one, I would have to add the new key to many servers as authorized keys,

So, I don’t want to get into a huge argument over the best way to deal with things, since everyone has their own use cases, but if that’s your only concern, you have a list of hosts that you want to put the key on, and you still have a key for another device, that shouldn’t be terribly difficult. Generate your new keypair for your new device. Then on a Linux machine, something like:

$ cat username-host-pairs.txt
me@host1
me@host2
me@host3
$ cat username-host-pairs.txt|xargs -n1 ssh-copy-id -i new-device-key-file-id_ed25519.pub

That should use your other device’s private key to authenticate to the servers in question and copy the new device’s pubkey to the accounts on the host in question. Won’t need password access enabled.

In fact, that’s generally what you want to do, since if one device gets lost or compromised, you just revoke access to the key for that device.

We have also produced treatments that work to some extent for some forms of cancer.

We don’t have a 100% reliable silver bullet that deals with everything with a simple five minute shot, but…

solving word hunger?

So, this was principally artificial selection to modify plants rather than genetic engineering (and I think that most people who say ‘biotech’ in 2026 mean genetic engineering), but there were a lot of people who did anticipate global famines until we made some substantial technological advancements with plants some decades back:

https://en.wikipedia.org/wiki/Green_Revolution

The Green Revolution, or the Third Agricultural Revolution, was a period during which technology transfer initiatives resulted in a significant increase in crop yields.[1][2] These changes in agriculture initially emerged in developed countries in the early 20th century and subsequently spread globally until the late 1980s.[3] In the late 1960s, farmers began incorporating new technologies, including high-yielding varieties of cereals, particularly dwarf wheat and rice, and the widespread use of chemical fertilizers (to produce their high yields, the new seeds require far more fertilizer than traditional varieties[4]), pesticides, and controlled irrigation.

At the same time, newer methods of cultivation, including mechanization, were adopted, often as a package of practices to replace traditional agricultural technology.[5] This was often in conjunction with loans conditional on policy changes being made by the developing nations adopting them, such as privatizing fertilizer manufacture and distribution.[4]

Both the Ford Foundation and the Rockefeller Foundation were heavily involved in its initial development in Mexico.[6][7] A key leader was agricultural scientist Norman Borlaug, the “Father of the Green Revolution”, who received the Nobel Peace Prize in 1970. He is credited with saving over a billion people from starvation.[8] Another important scientific figure was Yuan Longping, whose work on hybrid rice varieties is credited with saving at least as many lives.[9] The basic approach was the development of high-yielding varieties of cereal grains, expansion of irrigation infrastructure, modernization of management techniques, distribution of hybridized seeds, synthetic fertilizers, and pesticides to farmers. As crops began to reach the maximum improvement possible through selective breeding, genetic modification technologies were developed to allow for continued efforts.[10][11]

Studies show that the Green Revolution contributed to widespread eradication of poverty, averted hunger for millions, raised incomes, increased greenhouse gas emissions, reduced land use for agriculture, and contributed to declines in infant mortality.[12][13][14][15][16][17][excessive citations]

I have a black and white laser printer — a Brother, FWIW — that works great. It sits there and when I print the occasional document, flips on and quietly and quickly does its thing. I remember printers in past decades. Paper jams. Continuous-tractor feed paper having the tractor feeds rip free in the printer. Slow printing. Loud printing. Prints that smeared. Clogging ink nozzles on inkjets.

It replaced a previous Apple black-and-white laser printer from…probably the early 1990s that I initially got used which also worked fine and worked until the day I threw it out — I just wanted more resolution, which current laser printers could do.

The only thing that I can really beat the Brother up for is maybe that, like many laser printers, to cut costs on the power supply, it has a huge power spike in what it consumes when it initially comes on; I’d rather just pay for a better power supply. But it’s not enough for me to care that much about it, and if I really want to, I can plug it into power regulation hardware.

It’s not a photo printer, and so if someone wants to print photos, I can appreciate that a laser printer isn’t ideal for that, but…I also never print photos, and if I did at some point, I’d probably just hit a print shop.

For some workloads, yes. I don’t think that the personal computer is going to go away.

But it also makes a lot of economic and technical sense for some of those workloads.

Historically — like, think up to about the late 1970s — useful computing hardware was very expensive. And most people didn’t have a requirement to keep computing hardware constantly loaded. In that kind of environment, we built datacenters and it was typical to time-share them. You’d use something like a teletype or some other kind of thin client to access a “real” computer to do your work.

What happened at the end of the 1970s was that prices came down enough and there was enough capability to do useful work to start putting personal computers in front of everyone. You had enough useful capability to do real computing work locally. They were still quite expensive compared to the great majority of today’s personal computers:

https://en.wikipedia.org/wiki/Apple_II

The original retail price of the computer was US$1,298 (equivalent to $6,700 in 2024)[18][19] with 4 KB of RAM and US$2,638 (equivalent to $13,700 in 2024) with the maximum 48 KB of RAM.

But they were getting down to the point where they weren’t an unreasonable expense for people who had a use for them.

At the time, telecommunications infrastructure was much more limited than it was today, so using a “real” computer remotely from many locations was a pain, which also made the PC make sense.

From about the late 1970s to today, the workloads that have dominated most software packages have been more-or-less serial computation. While “big iron” computers could do faster serial compute than personal computers, it wasn’t radically faster. Video games with dedicated 3D hardware were a notable exception, but those were latency sensitive and bandwidth intensive, especially relative to the available telecommunication infrastructure, so time-sharing remote “big iron” hardware just didn’t make a lot of sense.

And while we could — and to some extent, did — ramp up serial computational capacity by using more power, there were limits on the returns we could get.

However, what AI stuff represents has notable differences in workload characteristics. AI requires parallel processing. AI uses expensive hardware. We can throw a lot of power at things to get meaningful, useful increases in compute capability.

• Just like in the 1970s, the hardware to do competitive AI stuff for many things that we want to do is expensive. Some of that is just short term, like the fact that we don’t have the memory manufacturing capacity in 2026 to meet need, so prices will rise to price out sufficient people that the available chips go to whoever the highest bidders are. That’ll resolve itself one way or another, like via buildout in memory capacity. But some of it is also that the quantities of memory are still pretty expensive. Even at pre-AI-boom prices, if you want the kind of memory that it’s useful to have available — hundreds of gigabytes — you’re going to be significantly increasing the price of a PC, and that’s before whatever the cost of the computation hardware is.

• Power. Currently, we can usefully scale out parallel compute by using a lot more power. Under current regulations, a laptop that can go on an airline in the US can have an 100 Wh battery and a 100 Wh spare, separate battery. If you pull 100W on a sustained basis, you blow through a battery like that in an hour. A desktop can go further, but is limited by heat and cooling and is going to start running into a limit for US household circuits at something like 1800 W, and is going to be emitting a very considerable amount of heat dumped into a house at that point. Current NVidia hardware pulls over 1kW. A phone can’t do anything like any of the above. The power and cooling demands range from totally unreasonable to at least somewhat problematic. So even if we work out the cost issues, I think that it’s very likely that the power and cooling issues will be a fundamental bound.

In those conditions, it makes sense for many users to stick the hardware in a datacenter with strong cooling capability and time-share it.

Now, I personally really favor having local compute capability. I have a dedicated computer, a Framework Desktop, to do AI compute, and also have a 24GB GPU that I bought in significant part to do that. I’m not at all opposed to doing local compute. But at current prices, unless that kind of hardware can provide a lot more benefit than it currently does to most, most people are probably not going to buy local hardware.

If your workload keeps hardware active 1% of the time — and maybe use as a chatbot might do that — then it is something like a hundred times cheaper in terms of the hardware cost to have the hardware timeshared. If the hardware is expensive — and current Nvidia hardware runs tens of thousands of dollars, too rich for most people’s taste unless they’re getting Real Work done with the stuff — it looks a lot more appealing to time-share it.

There are some workloads for which there might be constant load, like maybe constantly analyzing speech, doing speech recognition. For those, then yeah, local hardware might make sense. But…if weaker hardware can sufficiently solve that problem, then we’re still back to the “expensive hardware in the datacenter” thing.

Now, a lot of Nvidia’s costs are going to be fixed, not variable. And assuming that AMD and so forth catch up, in a competitive market, will come down — with scale, one can spread fixed costs out, and only the variable costs will place a floor on hardware costs. So I can maybe buy that, if we hit limits that mean that buying a ton of memory isn’t very interesting, price will come down. But I am not at all sure that the “more electrical power provides more capability” aspect will change. And as long as that holds, it’s likely going to make a lot of sense to use “big iron” hardware remotely.

What you might see is a computer on the order of, say, a 2022 computer on everyone’s desk…but that a lot of parallel compute workloads are farmed out to datacenters, which have computers more-capable of doing parallel compute there.

Cloud gaming is a thing. I’m not at all sure that there the cloud will dominate, even though it can leverage parallel compute. There, latency and bandwidth are real issues. You’d have to put enough datacenters close enough to people to make that viable and run enough fiber. And I’m not sure that we’ll ever reach the point where it makes sense to do remote compute for cloud gaming for everyone. Maybe.

But for AI-type parallel compute workloads, where the bandwidth and latency requirements are a lot less severe, and the useful returns from throwing a lot of electricity at the thing significant…then it might make a lot more sense.

I’d also point out that my guess is that AI probably will not be the only major parallel-compute application moving forward. Unless we can find some new properties in physics or something like that, we just aren’t advancing serial compute very rapidly any more; things have slowed down for over 20 years now. If you want more performance, as a software developer, there will be ever-greater relative returns from parallelizing problems and running them on parallel hardware.

I don’t think that, a few years down the road, building a computer comparable to the one you might in 2024 is going to cost more than it did in 2024. I think that people will have PCs.

But those PCs might running software that will be doing an increasing amount of parallel compute in the cloud, as the years go by.

They exist — and in fact, I have an Android tablet in my backpack right now — but a lot of people felt that they were going to become a major computing paradigm, and that hasn’t happened.

In practice, the PC today is mostly a conventional laptop. Hybrid laptops with touchscreen exist, but they aren’t the norm.

Mobile OS tablets also exist, but they haven’t managed to take over from smartphones or approach their marketshare, and there are fewer options on the market than there were a few years back; “mobile OS” tablets today are mostly, as best I can tell, a specialized device to use for video-watching with a larger screen than exists on a phone, with a larger screen and better built-in speakers, but without the sensors and radio suite. Not all that much uptake.

Oh, nice catch, thanks. I read it as “safe, without exploitable backdoors”, but that’s not what he was saying.

Flying cars. The idea has intuitive appeal — just drive like normal, but most congestion problems go away!

https://en.wikipedia.org/wiki/Flying_car

We’ve made them, but the tradeoffs that you have to make to get a good road vehicle that is also a good aircraft are very large. The benefits of having a dual-mode vehicle are comparatively limited. I think that absent some kind of dramatic technological revolution, like, I don’t know, making the things out of nanites, we’ll just always be better off with dedicated vehicles of the first sort or the second.

Maybe we could have call-on-demand aircraft that could air-ferry ground vehicles, but I think that with something on the order of current technology, that’s probably as close as we’ll get.

Well, it depends on the frequency range you’re talking about. In common usage, “radiation” often means something like ionizing radiation, but technically, UV light is a frequency of electromagnetic radiation.

https://en.wikipedia.org/wiki/Electromagnetic_radiation

In physics, electromagnetic radiation (EMR) or electromagnetic wave (EMW) is a self-propagating wave of the electromagnetic field that carries momentum and radiant energy through space.[1][2] It encompasses a broad spectrum, classified by frequency (inversely proportional to wavelength), ranging from radio waves, microwaves, infrared, visible light, ultraviolet, X-rays, to gamma rays.[3][4]

And if you include the ultraviolet frequency range, we did it decades ago:

https://www.dailymail.co.uk/sciencetech/article-1080042/Meet-Mr-Green-Genes--worlds-glow-dark-cat.html

Meet Mr Green Genes - the world’s first glow-in-the-dark cat

His eyes glow ghoulishly in the right light, just like any other cat’s - but so do his nostrils, gums and tongue.

Mr Green Genes of New Orleans in the U.S. is the country’s first ‘glow in the dark’ ginger tom.

In daylight he looks normal, but put him in a darkened room and switch on an ultraviolet light, and his face will beam out a bright green.

And so these humans would…be willing to do much to avoid the unchaining of these aquatic cats, you say?

https://en.wikipedia.org/wiki/One-time_pad

The one-time pad (OTP) is an encryption technique that cannot be cracked in cryptography. It requires the use of a single-use pre-shared key that is larger than or equal to the size of the message being sent.