I have an opinion about AI, which is that the LLM scam has yet to emerge. I know a lot of people on the fediverse are just automatically against LLMs and with what seems like a good set of reasons, but really they’re lacking in detail and just going along with a tide of opinion.
For most fediverse ‘LLM haters’ (or AI haters, but not all AI is an LLM) they’ll point to outrageous use of water for cooling, outrageous use of electricity, huge amounts of processing needed, insane amounts of GPU requirements, and so on. This is not even to mention the dodgy position on original effort and copyright and ownership of matter used in training. All seems bad. And it would be if this were to be believed.
But for a moment, let’s just not believe it.
The processing requirements - yes, you need high power GPUs for training. Why are we continually training LLMs? Most of the initial training was done long ago. Much of the training now is done by ‘inheriting’ the training from the initial models and refining it a lot, adding amounts of further training on top. Are we still training models as much as we used to be? More? Not as much? As much but more efficiently? Do we have any actual reporting on this as we stand today?
The amount of GPU needed (and consequently electricity) seems to me the thin end of a wedge-shaped iceberg of rabbit mines. Yes you ‘need’ a GPU to plough through a lot of numbers. Quite why we still need a ‘graphics processing unit’ to perform vector calculation is a quaint mystery of terminology – an early movement toward general purpose computing using the parallelism of GPUs used for shader calculation shifted the GPU away from purely graphics processing but didn’t really bring forth a recognised parallel computer platform (in the way we nearly had with the transputer in the 80s).
Today the tensor calculations used in AI and LLMs are pumped through GPUs. Perhaps we’re waiting for a massively parallel computer platform using optical computing. In the meantime, scaled-up parallel vector and tensor processors will have to do. Why though? Is that where the cartel money is, in keeping the GPU trade exactly as it is, only more of it? Surely something can come in from the side unexpectedly to eat this opportunity?
More than this though, I strongly guess or suspect that the amount of investment being sucked into the AI industry is completely describable as organised crime. That much money is extorted on the basis that huge data centres are required and that they’ll need to be filled with an arrangement of running GPUs and this is where the investment money will end up. I reckon that is mostly bullshit.
The data-centre argument is because the current ‘LLM as a Service’ model needs to attend to many millions of users all at once, and their prompt processing needs to be handled with minimum delay. We get that, yes. So it needs to be better than a standard web server with a complex web site. Yes. But wait, does it really? Really?
I don’t think the future is in AI as a Service so much as we’re being convinced it is, I think the future is more in local powerful models, not one big centralised provision. This is perfectly understandable – except if you’re behind running a big centralised provision, in which case your propaganda will laugh at local models and of course promote the single big ‘as a service’ provision.
I also doubt that a lot of the training is actually what they say it is. A lot of new models are trained on the results of old models. Not copied, but using an existing model, or more than one, to train ‘from’. Most of the energy use of LLMs I suspect has already happened, and there isn’t the need for an awful lot more. Except if you’re already structured for investment money funnelling in because training.
I also doubt that a lot of the results given in a ‘as a service’ model live over the centralised server provision is artificial – I am guessing that some of it is human-faked. And that’s where a lot of the investment money goes to – into paying humans to supplant deficiencies in the LLM scheme when run live for the entire population of the world that wants to use an online LLM service.
A local LLM can certainly do all that is required, but when the whole world wants to use a big centralised one, I’m guessing that having human assistance behind the scenes becomes necessary to ensure it all flows in time. Do we have any reporting on this front, I wonder?
I think the demands of LLMs – the training time and energy, the electricity to run it, the RAM, the GPU, etc, are real but the amount is inflated and when applied to centralised ‘as a service’ business structured projects, has been allowed to be outright deceptive at the least, and at most, almost mafia-like in terms of extortion, like a protection racket, designed to keep the already outmoded ‘centralised LLM as a Service’ con going.
Anyway, this is purely my guess. I’ve not looked into this at all.
#AI #LLM
ai
The courtroom battle between Elon Musk and Sam Altman heated up Monday when Musk’s AI expert Stuart Russell, a Cal-Berkeley computer science professor, took the stand. Russell co-signed an open letter in 2023 calling for a six-month pause in AI research. Here's more from @Techcrunch, including what Russell told jurors and Judge Yvonne Gonzalez Rodgers about the risks associated with AI:
#Tech #AI #ElonMusk #SamAltman #Technology #ArtificialIntelligence
OpenMythos: A theoretical reconstruction of the Claude Mythos architecture, built from first principles using the available research literature https://lobste.rs/s/zyjkpd #ai #reversing
https://github.com/kyegomez/OpenMythos
Realistic AI-generated climate disaster images decrease support for climate action when artificial origin is suspected
Policymakers and environmental advocacy organizations are increasingly using AI-generated images of climate disasters to advocate for climate interventions. Here we show that highly realistic AI-generated climate disaster images do not increase support for climate action
https://www.nature.com/articles/s44458-026-00092-0
#ClimateChange #UpheavalClimate #pollution #ecology #environment #climate
Software is inert without a human user, even though modern-day "agentic" apps are doing their best to squeeze human agency out of the loop. The focus on the tech and not how it is used has intensified an old phenomenon: interpassivity.
The vision tech has been pushing (software that "uses itself") has created a synthetic replacement for human agency. It is harder and harder to care, and that is by design.
https://productpicnic.beehiiv.com/p/the-newest-term-in-the-ai-lexicon-is-interpassivity
Y’all remember a couple weeks ago when I shared Privacy Guy’s article about #Anthropic being sketchy?
#Google said, Hold my beer, and dropped a 4 gig #ai weights file on every #chrome user. You can’t delete it, it reinstalls unless you can wizard your way through some obscure settings. And, the browser doesn’t use it, it ships queries to google cloud. It exists only so they can say it’s “local”.
“An engineering team at a large AI vendor decided that the user's machine is a deployment surface to be optimised for the vendor's product roadmap, not a personal device whose owner is the legal authority on what runs there.
The Anthropic case put a pre-authorisation for browser automation on around three million Claude Desktop user devices [19]. The Google case puts 4 GB of AI weights on, by my mid-band estimate, around 500 million Chrome user devices, with proportionally larger ePrivacy, GDPR, and environmental exposure.”
https://www.thatprivacyguy.com/blog/chrome-silent-nano-install
By now you've all probably heard about the latest shenanigans from Google and their love for in-browser AI features (if you don't, this is the story: https://www.theverge.com/tech/924933/google-chrome-4gb-gemini-nano-ai-features).
Our team has been inspecting the Chromium code and disabling stuff from the very first version of Vivaldi (we have some posts about this in our blog, such as https://vivaldi.com/blog/news/alert-no-google-topics-in-vivaldi/ or https://vivaldi.com/blog/no-google-vivaldi-users-will-not-get-floced/).
We've also been very outspoken about our dislike of the built-in AI trend in the browser industry, but in case there's still any doubts: yes, we disable all Gemini-related features, and we've been doing it for a while.
Had a blind person tell me today, offline, that they actually hope LLMs eliminate the need to go to websites because that would mean he would never have to fight an inaccessible website again, and I'm just sad forever now. It was somewhat similar to https://www.uxtigers.com/post/accessibility-generative-ui #AI #LLM #WebDev #Accessibility
The deadline to be included in the claim against Anthropic is 30 March. If you haven't already done so, submit your claim now. The Authors Guild have a useful guide.
https://authorsguild.org/advocacy/artificial-intelligence/what-authors-need-to-know-about-the-anthropic-settlement/
Google Just Bought a Stake in the Maker of Eve Online to Train Its AI Models
I just read this article about chess-like vs poker-like problems, and how poker-like problems are bad candidates for solution with LLM type models.
I'm looking for more reading like this about the underlying architecture, behavior, and future directions of the models and the cutting edge research around them. Does anyone have links they found valuable?
Just a little favor for his #billionaire #donor #TechBros
#Trump delays executive order on #AI #oversight hours before planned signing
The White House had already sent out invitations to the event, where Trump had been expected to sign an order increasing government scrutiny of new #ArtificialIntelligence models.
#law #tech #business #regulation #MentalHealth #plutocracy #aristocracy #technocracy
https://www.washingtonpost.com/technology/2026/05/21/white-house-tore-down-ai-rules-now-its-building-new-defenses/
Kagi started as an AI company that wanted to slurp up the internet to provide a question "answering" service not unlike what Google is proposing to replace web search with. Perhaps they've toned this rhetoric down a bit on their blog recently but there's no evidence I'm aware of that the business has changed mission. All of this is still available on Kagi's own blog---including the fact that they used to be kagi.ai---yet somehow it's controversial to point it out. If you're looking for a web search engine that isn't likely to turn into a slop extruder, Kagi is probably not going to be the one. Try @Mojeek or Marginalia. This list might be helpful too.
#web #search #dev #tech #software #AI #Kagi #WebSearch #InternetSearch #InformationRetrieval
ChatGPT was never Google’s biggest threat; it was always its own hubris.
With Search now being sacrificed on the altar of AI dominance, the time has come for users to get serious about moving off Google services. It’s not only destroying its products; it’s trying to further degrade the web itself.
"‘No one has done this in the wild’: study observes #AI replicate itself"
I find this article to be sensationalistic, but I agree there is a reckoning coming
People conjure dramatic scenarios like the movies, but I feel if AI does fuck us up, it will be according to the most boring and mundane of ways
My particular terror is turning all of #socialMedia into a wasteland of exquisite mechanized #psyop for #politics
Until such time, unplugging the damn things can work
#Digg used to be a decent platform. They made mistakes, shut down, and moved on.
Fast forward — they start up *again*, seemingly redoing their original thing, only to shut it all down, and launch and entire site dedicated to #AI slop, scraped from places like xitter.
TL;DR — Kevin is a soulless, grifting chode.
One thing I thought #LLMs were good for was translation. Apparently #Gemini and others aren’t that great at that either.
#Wikipedia restricted contributors from a nonprofit called the Open Knowledge Association (#OKA) after editors discovered #AI-assisted translations added factual errors and incorrect citations.
As predicted, humans will be relegated to cleaning up the mess LLMs leave behind, for salaries far below the value of full-time employment to do the job properly.
[…] Zimmerman added that if this method proves insufficient, OKA is considering introducing formal peer‑review mechanisms.
https://www.404media.co/ai-translations-are-adding-hallucinations-to-wikipedia-articles/
New development in Elon Musk’s trial against Sam Altman. A federal court in Oakland, Calif., heard a former OpenAI employee and board member say the company’s efforts to push AI products into the marketplace compromised its commitment to AI safety. @Techcrunch has more:
#Tech #AI #Musk #Altman #OpenAI #Technolgy #ArtificialIntelligence
[2606.03811] AI Agents Enable Adaptive Computer Worms
https://arxiv.org/abs/2606.03811
Forget all previous threats. Forget Mythos.
Given the current state of the infrastructure and all the bugs in firewalls, perimeter security doesn't protect you seriously.
If you can't turn off the computer because it controls your critical infrastructure you have a hard problem now.
"Proprietary" means having owner(s). If the maintainers are the only ones allowed to introduce changes, they are establishing an ownership relationship over the codebase. I.e., it's a proprietary project, and that is the sense in which it's closed.
This is the destiny of most projects that go AI, in my opinion.
https://exquisite.social/users/thomholwerda/statuses/116697078838020135
https://ladybird.org/posts/changing-how-we-develop-ladybird/
A new study in The Lancet shows that the rate of fake citations increased more than 12x between Jan 2023 and Feb 2026.
https://www.thelancet.com/journals/lancet/article/PIIS0140-6736(26)00603-3/fulltext
" #France shifts away from #Palantir, towards ‘ #AI #sovereignty’"
https://www.computing.co.uk/news/2026/ai/france-shifts-away-from-palantir-towards-ai-sovereignty
👏 👏 👏
Keep it up #Europe
But please do me a favor
Don't replace #USA #techbro shit with... USA-style techbro shit (like this #W #Bluesky vomitorium)
And if I need to explain to you what I mean... no I don't think I need to do that. You feel what that means in your bones
I say this as an American
In 2024 we learned about the IDF's AI system #Lavender that ranked the entire population of #Gaza by “probability of militant affiliation". With a targeting system called "Where's Daddy", so they could hit #AI determined targets at home, the #IDF allowing up to 100 civilians killed per "militant". The rubble of Gaza is the result.
I tell you that story to tell you this one.
Peter Thiel’s #Palantir sells
#ELITE which pulls data from the IRS, the SSA, DMV, Medicaid, utility bills, license-plate readers and data brokers to create a map with dossiers and a “confidence score” to each person’s current address.
#Pentagon rolled out a $1.5 trillion budget request that contained a 24,000 percent increase, from $225 million last year to $54.6 billion this year, for an outfit called the Defense Autonomous Warfare Group.
It’s earmarked to build out AI-driven autonomous human-killing systems inside the Special Operations Command at MacDill AFB, Florida.