tbh i somehow didnt even realize that wikipedia is one of the few super popular sites not trying to shove ai down my throat every 5 seconds
i’m grateful now
Christ, I miss when I could click on an article and not be asked to sign up for it.
Oh, right! Thanks for reminding me. I tried to archive it the last time but it took forever.
Edit. There ya’ go: https://archive.is/oWcIr
As I have adblock mostly because of the abuse of trackers, I understand people trying to monetize their work.
Fuck AI
He is nobody to Wikipedia now. He also failed to create a news site and a micro SNS.
He can also stick AI inside his own ass
Sit down Jimmy. Wikipedia has enough problems already, it doesn’t need more to be added by AI.
I will stop donating to Wikipedia if they use AI
What’s funny is that for enormous big systems with network effects we are trying to use mechanisms intended for smaller businesses, like a hot dog kiosk.
IRL we have a thing for those, it’s called democracy.
In the Internet it’s either anarchy or monarchy, sometimes bureaucratic dictatorship, but in that area even Soviet-style collegial rule is something not yet present.
I’m recently read that McPherson article about Unix and racism, and how our whole perception of correct computing (modularity, encapsulation, object-orientation, all the KISS philosophy even) is based on that time’s changes in the society and reaction to those. I mean, real world is continuous and you can quantize it into discrete elements in many ways. Some unfit for your task. All unfit for some task.
So - first, I like the Usenet model.
Second, cryptography is good.
Third, cryptographic ownership of a limited resource is … fine, blockchains are maybe not so stupid. But not really necessary, because one can choose between a few versions of the same article retrieved, based on web of trust or whatever else. No need to have only one right version.
Fourth, we already have a way to turn sequence of interdependent actions into state information, it’s called a filesystem.
Fifth, Unix with its hierarchies is really not the only thing in existence, there’s BTRON, and even BeOS had a tagged filesystem.
Sixth, interop and transparency are possible with cryptography.
Seventh, all these also apply to a hypothetical service over global network.
Eighth, of course, is that the global network doesn’t have to be globally visible\addressable to operate globally for spreading data, so even the Internet itself is not as much needed as the actual connectivity over which those change messages will propagate where needed and synchronize.
Ninth, for Wikipedia you don’t need as much storage as for, say, Internet Archive.
And tenth - with all these one can make a Wikipedia-like decentralized system with democratic government, based on rather primitive principles, other than, of course, cryptography involved.
(Yes, Briar impressed me.)
EDIT: Oh, about democracy - I mean technical democracy. That an event (making any change) weren’t valid if not processed correctly, by people eligible for signing it, for example, and they are made eligible by a signed appointment, and those signing it are made eligible by a democratic process (signed by majority of some body, signed in turn). That’s that blockchain democracy people dreamed at some point. Maybe that’s not a scam. Just haven’t been done yet.
How do you prevent sybil attacks without making it overly expensive to vote?
How do you use Sybil attack for a system where the initial creator signs the initial voters, and then they collectively sign elections and acceptance of new members and all such stuff?
Doesn’t seem to be a problem for a system with authorized voters.
Flood them with AI-generated applicants.
So why would they accept said AI-generated applicants?
If we are making a global system, then confirmation using some nation’s ID can be done, with removing fakes found out later. Like with IRL nation states. Or “bring a friend and be responsible if they are a fake”. Or both at the same time.
Would every participant get to see my government-issued ID?
One can elect a small group which will and will sign its connection to something intermediate. Then only they will.
Wikipedia already has a decades operating cost of savings.
No they don’t because they blast it on inflated exec wages.
Why don’t they blast execs and reduce the expenses.
jimmy wales is also the president and co-founder of fandom
to give you an idea of who that guy is
Obligatory plug for BreezeWiki. Makes that shit actually usable.
I mean, the Wikipedia page does say it was sold in 2018. Not sure how it was before but it’s not surprising that it enshittified by now.
I guess in his defense it wasn’t too bad before 2018, as far as I can remember. Most of the enshittification of fandom I can remember has happened since.
Oh gross
Why?
Fandom (previously Wikia) is an extremely shitty service with low-quality wikis mostly consisting of content copied from independent wikis and a terrible layout that only exists to amplify their overwhelming advertising.
my one weird trick for using fandom.com is to disable javascript for that domain.
While this is true, the majority of the wikis are not at all low quality. Some are the only ones existing for a topic. The wikis are community-based, after all.
But its easy to vandalize and is highly profit-driven. The fandom wikis are filled with ads that absolutely destroy navigation. Infamous is the video ad that scrolls you up automatically in the middle of reading once it finishes. You have to pause it to read the article with no interruption.
they captured the “niche wiki” market as wikia, then rebranded and started serving shittons of ads. the vim wiki is unusable these days because it runs like ass and looks like a gamer rgb nightmare
There’s an addon for that, Indie Wiki Buddy.
It tries to redirect you to non fandom/fextralife wikis if they exist, and if not, it proxies fandom wikis through BreezeWiki which just displays the content.And I’ll take this opportunity to plug Hohser and the uBlock AI blocklist as well.
Oh yeah that website’s pretty great It has really in depth wiki about games like https://fallout.fandom.com/wiki/Caesar’s_Legion
So I guess you mean that Wales guy is pretty great then
Oh, you mean the https://fallout.wiki/wiki/Caesar's_Legion ?
Yup, Fallout Wiki has a pretty crazy history. I don’t remember if they were originally a Fandom wiki, but at some point they definitely went “well, we don’t want to go with Fandom, we’ll go with Curse wiki host instead.” Then Fandom bought Curse wikis and put all of them under Fandom banner anyway.
The independent Fallout Wiki is basically where the actual community is right now, the Fandom wiki is just there to confuse passers-by with their high search engine rank. Fandom has the policy that the community can fork a wiki and go elsewhere, but they will not close down the Fandom wiki, so good luck with your search rankings.
Many game communities have opted for the “unbridled vandalism” strategy to push people away from fandom. Just replace all the articles with plausible lies.
The “fandom” one is much more complete ?
I mean, they’re both pretty great,
From the search engine if I wanted to know about in-game faction,
I’d just pick which ever appeared first.
and it’d be fine either waySo why would “Chloé 🥕@lemmy.blahaj.zone”
think they can just point at it and imagine any random people would even know
what she “who that guy is” means just because he’s associated with that wiki ?And that my innocuous comment
would triggers the nerds with such an unanimously negative response ?
Wales’s quote isn’t nearly as bad as the byline makes it out to be:
Wales explains that the article was originally rejected several years ago, then someone tried to improve it, resubmitted it, and got the same exact template rejection again.
“It’s a form letter response that might as well be ‘Computer says no’ (that article’s worth a read if you don’t know the expression),” Wales said. “It wasn’t a computer who says no, but a human using AFCH, a helper script […] In order to try to help, I personally felt at a loss. I am not sure what the rejection referred to specifically. So I fed the page to ChatGPT to ask for advice. And I got what seems to me to be pretty good. And so I’m wondering if we might start to think about how a tool like AFCH might be improved so that instead of a generic template, a new editor gets actual advice. It would be better, obviously, if we had lovingly crafted human responses to every situation like this, but we all know that the volunteers who are dealing with a high volume of various situations can’t reasonably have time to do it. The templates are helpful - an AI-written note could be even more helpful.”
That being said, it still reeks of “CEO Speak.” And trying to find a place to shove AI in.
More NLP could absolutely be useful to Wikipedia, especially for flagging spam and malicious edits for human editors to review. This is an excellent task for dirt cheap, small and open models, where an error rate isn’t super important. Cost, volume, and reducing stress on precious human editors is. It’s a existential issue that needs work.
…Using an expensive, proprietary API to give error prone yet “pretty good” sounding suggestions to new editors is not.
Wasting dev time trying to make it work is not.
This is the problem. Not natural language processing itself, but the seemingly contagious compulsion among executives to find some place to shove it when the technical extent of their knowledge is occasionally typing something into ChatGPT.
It’s okay for them to not really understand it.
It’s not okay to push it differently than other technology because “AI” is somehow super special and trendy.
This is another reason why I hate bubbles. There is something potentially useful in here. It needs to be considered very carefully. However, it gets to a point where everyone’s kneejerk reaction is that it’s bad.
I can’t even say that people are wrong for feeling that way. The AI bubble has affected our economy and lives in a multitude of ways that go far beyond any reasonable use. I don’t blame anyone for saying “everything under this is bad, period”. The reasonable uses of it are so buried in shit that I don’t expect people to even bother trying to reach into that muck to clean it off.
This bubble’s hate is pretty front-loaded though.
Dotcom was, well, a useful thing. I guess valuations were nuts, but it looks like the hate was mostly in the enshittified aftermath that would come.
Crypto is a series of bubbles trying to prop up flavored pyramid schemes for a neat niche concept, but people largely figured that out after they popped. And it’s not as attention grabbing as AI.
Machine Learning is a long running, useful field, but ever since ChatGPT caught investors eyes, the cart has felt so far ahead of the horse. The hate started, and got polarized, waaay before the bubble popping.
…In other words, AI hate almost feels more political than bubble fueled. If that makes any sense. It is a bubble, but the extreme hate would still be there even if it wasn’t.
Crypto was an annoying bubble. If you were in the tech industry, you had a couple of years where people asked you if you could add blockchain to whatever your project was and then a few more years of hearing about NFTs. And GPUs shot up in price. Crypto people promised to revolutionize banking and then get rich quick schemes. It took time for the hype to die down, for people to realize that the tech wasn’t useful, and that the costs of running it weren’t worth it.
The AI bubble is different. The proponents are gleeful while they explain how AI will let you fire all your copywriters, your graphics designers, your programmers, your customer support, etc. Every company is trying to figure out how to shoehorn AI into their products. While AI is a useful tool, the bubble around it has hurt a lot of people.
That’s the bubble side. It also gets a lot of baggage because of the slop generated by it, the way it’s trained, the power usage, the way people just turn off their brains and regurgitate whatever it says, etc. It’s harder to avoid than crypto.
God I had coworkers that had never used a vr headset claiming the metaverse was going to be the next big thing. I wish common sense was common.
“The metaverse” changed it’s definition depending on who you talked to. Some definitions didn’t even include VR.
“AI” also changes it’s definition depending on who you talk to.
Vague definitions = hype
Yeah, you’re right. My thoughts were kinda uncollected.
Though I will argue some of the negatives (like inference power usage) are massively overstated, and even if they aren’t, are just the result of corporate enshittification more than the AI bubble itself.
Even the large scale training is apparently largely useless: https://old.reddit.com/r/LocalLLaMA/comments/1mw2lme/frontier_ai_labs_publicized_100kh100_training/
I believe that the bad behavior of corporate interests is often one of the key contributors to these financial bubbles in every sector where they appear.
To say that some of the bad things about this particular financial bubble are because of a bunch of companies being irresponsible and/or unethical seems not to acknowledge that one is primarily caused by the other.
So… I actually proposed a use case for NLP and LLMs in 2017. I don’t actually know if it was used.
But the usecase was generating large sets of fake data that looked real enough for performance testing enterprise sized data transformations. That way we could skip a large portion of the risk associated with using actual customer data. We wouldn’t have to generate the data beforehand, we could validate logic with it, and we could just plop it in the replica non-prodiction environment.
At the time we didn’t have any LLMs. So it didn’t go anywhere. But it’s always funny when I see all this “LLMs can do x” because I always think about how my proposal was to use it… For fake data.
That being said, it still wreaks of “CEO Speak.”
I think you mean reeks, which means to stink, having a foul odor.
Those homophones have reeked havoc for too long!
Waves hands “You didn’t see anything.”
Thank you. Glad to know I am not the only one that got triggered, lol.
That being said, it still wreaks of “CEO Speak.” And trying to find a place to shove AI in.
I don’t see how this is “shoved in.” Wales identified a situation where Wikipedia’s existing non-AI process doesn’t work well and then realized that adding AI assistance could improve it.
Neither did Wales. Hence, the next part of the article:
For example, the response suggested the article cite a source that isn’t included in the draft article, and rely on Harvard Business School press releases for other citations, despite Wikipedia policies explicitly defining press releases as non-independent sources that cannot help prove notability, a basic requirement for Wikipedia articles.
Editors also found that the ChatGPT-generated response Wales shared “has no idea what the difference between” some of these basic Wikipedia policies, like notability (WP:N), verifiability (WP:V), and properly representing minority and more widely held views on subjects in an article (WP:WEIGHT).
“Something to take into consideration is how newcomers will interpret those answers. If they believe the LLM advice accurately reflects our policies, and it is wrong/inaccurate even 5% of the time, they will learn a skewed version of our policies and might reproduce the unhelpful advice on other pages,” one editor said.
It doesn’t mean the original process isn’t problematic, or can’t be helpfully augmented with some kind of LLM-generated supplement. But this is like a poster child of a troublesome AI implementation: where a general purpose LLM needs understanding of context it isn’t presented (but the reader assumes it has), where hallucinations have knock-on effects, and where even the founder/CEO of Wikipedia seemingly missed such errors.
Don’t mistake me for being blanket anti-AI, clearly it’s a tool Wikipedia can use. But the scope has to be narrow, and the problem specific.
Honestly, translating the good articles from other languages would improve Wikipedia immensely.
For example, the Nanjing dialect article is pretty bare in English and very detailed in Mandarin
This is the goal of Abstract Wikipedia. https://meta.wikimedia.org/wiki/Special:MyLanguage/Abstract_Wikipedia
You can do that, that’s fine. As long as you can verify it is an accurate translation, so you need to know the subject matter and the target language.
But you could probably also have used Google translate and then just fine tune the output yourself. Anyone could have done that at any point in the last 10 years.
As long as you can verify it is an accurate translation
Unless the process has changed in the last decade, article translations are a multi-step process, which includes translators and proof-readers. It’s easier to get volunteer proof-readers than volunteer translators. Adding AI for the translation step, but keeping the proof-reading step should be a great help.
But you could probably also have used Google translate and then just fine tune the output yourself. Anyone could have done that at any point in the last 10 years.
Have you ever used Google translate? Putting an entire Wikipedia article through it and then “fine tuning” it would be more work than translating it from scratch. Absolutely no comparison between Google translate and AI translations.
Putting an entire Wikipedia article through it and then “fine tuning” it would be more work than translating it from scratch.
That depends on if you are capable of translating the language if you don’t know the language then the translator will give you a good start.
Google translate is horrendously bad at Korean, especially with slang and accidental typos. Like nonsense bad.
Same in Hungarian, machine translation still often gives hilariously bad results. It’s especially prone to mixing up formal and informal ‘you’ within the same paragraph, something which humans never do. At least it’s easy to tell when a website is one of those ‘auto-translated to 30 languages’ content mill.
I recently have edited a small wiki page that was obviously written by someone that wasn’t proficient in English. I used AI to just reword what was already written and then I edited the output myself. It did a pretty good job. It was a page about some B-list Indonesian actress that I just stumbled upon and I didn’t want to put time and effort into it but the page really needed work done.
Wikipedia’s translation tool for porting articles between languages currently uses google translate so I could see an LLM being an improvement but LLMs are also way way costlier than normal translation models like google translate. Would it be worth it? And also would the better LLM translations make editors less likely to reword the translation to make it’s tone better?
You can use an LLM to reword the translation to make the tone better. It’s literally what LLMs are designed to do
if jimmy wales puts ai in wikipedia i stg imma scream
The editor community rejected the idea so overwhelmingly, that Wikipedia paused the planned experiment in June, hopefully for good.
Why is leadership always so vapid and disconnected from reality?
Because this is one of the rare times he sat down at the keyboard to do the real work being done by people in this organization and he realized that it’s hard and he wants a shortcut. He sees his time as more valuable and sees this task as wasting his time, but it is their primary task and one they do as volunteers because they are passionate about it. He’s not going to get a lot of traction with them telling them the thing they do for free because they love it isn’t worth anyone’s time.
I swear these people have never been around a cathedral and thought about how it was built.
I think commenters here don’t actually do Wikipedia. Wales was instrumental in Wikipedia’s principles and organization besides the first year of Sanger. He handpicked the first administrators to make sure the project would continue its anarchistic roganization and prevent a hierarchy from having a bigger say in content matters.
I would characterize Wales as a long-retired leader rather than leadership.
Because that’s what being in a position of power does to a mf
Remember you can download all of Wikipedia in your language and safely store it on a drive buried in your backyard, for after they rewrite history and eliminate freedom of speech.
Already got it downloaded. It’s only like 100 - 150 gigabytes or something like that. Got it on my PC, my laptop, and my external hard drive. I don’t trust the powers that be to keep it intact anymore so I’d rather have my own copy, even if outdated.
What about any of this remotely connects to “rewriting history and eliminating freedom of speech?”
Proprietary AI means corpo involvement, and usually it’s the really actively awful sort of techbros, this involvement gives them some power, and this power is a threat. Whether it materializes or not, living in the world we do now, it’s only right to be wary. I already figured Wikipedia was on its way out a few months ago and downloaded both the kiwi program reader version and the raw xml dump + file for truly apocalyptic situations.
There are lots of non-proprietary AI models out there, some of them comparable in quality to ChatGPT. Wikipedia could run it themselves if they wanted, no “corpo involvement.”
Some people can’t really stop seeing conspiracies everywhere.
As long as billionaires are campaigning to destroy it, there is no place for that comment you made.
Pathetic…
I don’t think an existing conspiracy is necessary, it’s just a cheap way to help protect yourself and others against something that could happen one day.
I can understand that. But should one apply this to every aspect of their life, they’ll just be living in a cave.
The problem with LLMs and other generative AI is that they’re not completely useless. People’s jobs are on the line much of the time, so it would really help if they were completely useless, but they’re not. Generative AI is certainly not as good as its proponents claim, and critically, when it fucks up, it can be extremely hard for a human to tell, which eats away a lot of their benefits, but they’re not completely useless. For the most basic example, give an LLM a block of text and ask it how to improve grammar or to make a point clearer, and then compare the AI generated result with the original, and take whatever parts you think the AI improved.
Everybody knows this, but we’re all pretending it’s not the case because we’re caring people who don’t want the world to be drowned in AI hallucinations, we don’t want to have the world taken over by confidence tricksters who just fake everything with AI, and we don’t want people to lose their jobs. But sometimes, we are so busy pretending that AI is completely useless that we forget that it actually isn’t completely useless. The reason they’re so dangerous is that they’re not completely useless.
It’s almost as if nuance and context matters.
How much energy does a human use to write a Wikipedia article? Now also measure the accuracy and completeness of the article.
Now do the same for AI.
Objective metrics are what is missing, because much of what we hear is “phd-level inference” and it’s still just a statistical, probabilistic generator.
https://www.pcmag.com/news/with-gpt-5-openai-promises-access-to-phd-level-ai-expertise
It is completely useless as presented by the major players who atrocities trying to jam models that are trying to everything at the same time and that is what we always talk about when discussing AI.
We aren’t talking about focused implementations that are Wikipedia to a certain set of data or designed for specific purposes. That is why we don’t need nuance, although the reminder that we aren’t talking about smaller scale AI used by humans as tools is nice once in a while.
WikipedAI
