I hope the next AI winter is soon and all the tech bros get banished to Wumpus World.
AI would actually be good if it weren’t for capitalism.
This is a true statement. Chatbots, image generators, and music generators have become the public face of AI because they are easily packaged and sold as mass-market products. Meanwhile, socially useful applications (systems that translate sign language using object recognition models, assist blind and visually impaired people by describing their surroundings again using object recognition, or provide real-time subtitles through smart glasses for deaf and hard-of-hearing users using language models, etc.) are often underfunded in comparison to the ridiculous bubble there is at current because they are less immediately profitable.
Technology does not develop or operate outside society. AI is shaped by the material conditions, class relations, and economic system in which it is produced. Under capitalism, investment is directed primarily toward profit, market expansion, labour reduction, surveillance, and the accumulation of private power. The problem is not some abstract “internal logic” of AI, but the internal logic of capitalism determining which forms of AI are developed, who controls them, and how they are used.
The original Luddites had a real grievance with machinery being used by owners to deskill workers, lower wages, and destroy livelihoods. However rejecting the machinery itself was the wrong answer to a problem rooted in class power and ownership. Neo-Luddism repeats that mistake. AI is a tool. The fact that it is currently used largely for nonsense, exploitation, surveillance, and other harmful ends is a systemic problem, not a tool problem.
Do you have information on energy usage between the two types?
I'm trying to take a grounded stance on technology for my local group and hoping to demonstrate how there is a place for this technology if it is heavily regulated. And other systems used locally. Based off of thing I've read here and there. However I do not know if I'm prepared enough or how to tackle the mountain ahead of me.
Of course this is not your burden and feel free to ignore if ask is too great.
Do you have information on energy usage between the two types?
I’m not sure what you mean by “the two types.” These are not necessarily two distinct kinds of AI so much as the underlying technologies being deployed for different purposes.
The issue with AI’s energy cost (in the west) is that it is currently immense while often providing very little social value. That cost is made worse by its continued dependence on fossil fuels, a dependence rooted in the fact that capitalism stunted renewable-energy buildout across the imperial core for decades.
Sorry. Its still early for me and I'm suffering through a flare up.
In my mind two types is like I know there is open source but I'm not sure what that means. Then there is the Chinese model which may also be open source? Then there is the tech bros like Google and amazon who obviously do not have people needs at the for front.
And there is like what. What is AI in terms of language. What makes these new systems different then the things we were doing before chatgpt came into our lives? Like we always had bots.
Ai really isn't my speciality so I don't think I can answer most of this.However I'll give what I know a shot.
Open-source AI models (or open-weight models as I think they're technically called) allow people to download the model’s trained parameters and run, modify and fine-tune it themselves rather than relying entirely on the developer’s platform. Many Chinese developers, including DeepSeek and Qwen, release model weights, code and technical papers, operating partly like open research labs, although not every Chinese model is open. By contrast most of the large western firms keep their leading models proprietary instead selling access through their platforms or API's.
As for the technical minutia of your second question I am unsure beyond the fact it's a lot of matrix maths.
Thank you very much for the explanations! I appreciate you!
I’m not the original person but the reason we have chatbots and image generators and the whole concept of AI slop is because the “AI” sector got chosen as a vessel for speculation. I strongly question the utility/ethics/value of chatbots, versus the applications for this sector if it was not being turned into the ersatz centerpiece of global capitalism. I think you’re humoring these speculators when you try to understand it through the lens of sapience.
In a few years it will be some other tech sector where a lack of progress can be hidden behind billions from international finance gamblers. If we don’t have a 100th Anniversary Black Tuesday Reenactment.
Thank you!
stop going on reddit
Trueanon users will eventually show up to defend usage of slurs
Reddit moment
eventually
It’s immediate
I was making a reference to something
You mean the struggle session a month or two back?
look up "Franklin will eventually show up to defend his home", funny video
Reddit is still reddit. Odds are they are cops, or bots, or bot cops
Paul Cop, Mall Bot
there are so many ai bro leftists on grad and ml too
it's genuinely so disheartening
Almost as bad a arguing with blockchain socialist that were trying to sell people on the idea that smart contracts/dapps are the future of worker organizing and coops.
Ok but like, Hexbear coin will be different guys. This one won't be a rugpull I swear please give me money. /j
to the moon
Graph is green so you should invest.
Where is Blake when you need him?
People always get upset when I talk about my AI usage as a teacher, but I teach ELL high school students and any given year I have at least three languages in a hour, not to mention different combinations of at least three languages in an hour. Translating material is way easier with LLMs. My school bought me a better MacBook so I can use offline local models now. My official stance is push for offline local model adoption and data centers in space.
i must be fatally irony poisoned because this to me is almost indistinguishable from a "bit", but apparently it's a real person's real opinion
oh no there's worse stuff
The left cares so much about AI because leftists are mainly in the Professional Managerial class stratum of the working class who are most under threat by AI. (intellectual labourers and shit). It's a class and position defensive reflex, not an actual analysis. Telling them this makes them very upset because it exposes the self interest.
It's also why the more manual labouring working classes, often conservatives, don't care about AI and even enjoy it, it doesn't threaten their work.
It's only a class analysis of Marxism that can rise above it and see that it's a progressive technology being abused for profit not people.
One interesting thing is it can reconstruct ancient languages by pattern matching. Hello fully reconstructed Proto Indo European.
fuck you it can. stembros can't comprehend language or history, it's all math and puzzles
Genuinely, anti AI leftists are just reactionary luddites without a Marxist class analysis
A peak inside the minds of decrepit ex-Chapoids 10 years later. Who thought they were gonna get some social democracy bennies. May Brooklyn burn!
Oh yeah that one takes the cake.
I would assume that "dead internet theory" applies to reddit, and most of the accounts there these days are just bots, and those same bots probably are programmed to come to the defence of AI whenever a post talks negatively about it.
LLMs should have stuck to data-sorting the way wifi receptors should have stayed to like phones, general purpose computers, etc. But the need to force it into everything has people totally misunderstanding what the purpose of it is. They think LLM slop is useful for music and etc. generation the same way they think there must be a use for your BBQ to connect to the internet over the 1 incredibly stupid niche scenario they imagine in their head.
Or how whey powder should have stuck to "protein powder" or whatever the fuck. Instead of forcing it into granola bars, chips, cereal as "super-healthy protein food" that you 'need.'
LLMs do not sort data though.
sorting, pattern recognizing, pattern creating, whatever.
My wife says she’s found the Adobe AI is actually pretty decent at taking large files with a lot of data presented in graphical form and summarizing it in text. Minimal generative content, only working with a narrow scope, so less opportunities for digital hallucinations.
There is plenty of opportunities for hallucinations. Sometimes those systems just ignore the files as make up the results.
I said less, not none. That particular AI will give the relevant page citation(s) for any stat or claim it makes so you can correct for errors, but obviously that doesn’t account for any data it just skipped so there’s still a possibility for errors of omission.
I’ll also note, as I think this is an under appreciated aspect of the AI narrative, is my wife is not some AI sycophant. She hates when people use AI to “write” an email. However, she is horrendously understaffed and gets way too much work dumped on her because she’s the only one that seems to have any institutional knowledge and gets things done without drama. So she’d love to go through these documents manually. But when you’ve got eight proposals dumped on your desk, each hundreds of pages of dense technical details, and are told “get them all evaluated by the end of the week,” there’s not much of an option there. When there’s more fallout from not getting the review done in time than there is from some bad data making it through the analysis of the AI summary, it’s not surprising that people are using it out of necessity.
Sure if correctness doesn't matter it's fine.
That sub turned me off when there was an entire thread about being sexpats in Central America. The type of foreigners who go home bragging about how all the “Latina baddies” were on their dick are usually ugly as shit and go for girls under 18, middle aged women, or prostitutes that they lie about being some random they met at the club.
The attractive guys who get baddies usually end up with women in their age range and comparative tax bracket.
Edit: forgot to add that most of the baddies they hook up with are other tourists or expats
I think they can be useful for things like economic planning but they should never, ever be used for art. It should be a predictive tool for particular industries working under direct human supervision and nothing more.
How, exactly, is gen "AI" useful for economic planning?
I can think of many a reason why various computer software/hardware is useful for economic planning. A spreadsheet, a database, a network, a scripting language, a statistics package, a graphing library: all useful. An LLM? How does that help?
As far as I understand it, it can make can automate particular calculations in ways other machines cannot. I'm not particularly knowledgeable on it though, I'm just going off of what I've heard from other leftists. Since the machine is effectively just a plagiarism device that learns from what it's seen before, it can automate certain things and make predictions based on that.
Some deep learning algorithms are able to uncover important patterns in vast datasets, but those have been in development for decades and aren't genAI. GenAI is an incredibly elaborate "tricking into thinking that the horse can actually count" gag.
Ahhh ok. For clarification, are those deep learning algorithms also LLMs but are considered separate from GenAI, or are they a different category of model entirely. I just want to make sure I know the correct taxonomy.
LLMs are sort of like a bastard child outgrowth of machine learning systems. They aren't necessarily hot garbage -- e.g., DeepSeek is surprisingly good at scraping and summarizing research papers that have been fed into it -- but the general-purpose commercial shit like ChatGPT, Bard, Copilot, etc. are all more or less snake oil. Doing this stuff with manuals, technical whitepapers, and so forth is probably viable, but once they started feeding in social media posts -- even StackOverflow -- they lost the plot entirely. I say this as a senior-level software developer who constantly has to look shit up because I bounce between too many languages/platforms and nearly always need a refresher for whichever one I am currently trying to beat into submission, and I have been skimming the Google AI overview shit and checking its work more often than not lately. It doesn't always understand what I am looking for and tries to shit something out of left field anyway, so I just go straight to whatever Reddit/Stack/Baeldung/NerdRanch links pop up in the first few pages of results, but when it does "get" it, it's pretty close. If it's doing anything more than summarizing a Linux man page, I still click through to its source links because the highest-updooted answer (which is what the overview uses) isn't always the most correct for what I'm doing.
Regarding other actual uses, I think it was @microfiche@hexbear.net a few weeks back that had an anecdote about using one of the public LLMs to lay out some plumbing plans for a residential space given a set of codified rules, and the slop machine came out surprisingly close to the mark because it had so many guard rails around it (due to the building/plumbing code). I could see it working as a sanity check for tradespeople, civil engineers, and architects if they're running specialized models and the LLM is ultimately just a user interface. We're not really there in the US though. Shit's too unregulated and consumes entirely too much energy for what is still ultimately a novelty.
For whatever we use it for, it should certainly never take acres of land and comical quantities of water to use it.
I think that’s directly tied to the “feed it everything and the kitchen sink” approach of the general purpose, household name AI. It’s a brute force way of training the AI, and running that analysis on such gigantic data sets inevitably means huge power draws.
In computer science, starting in the 50s, there was a discipline called "artificial intelligence". Despite some interesting things coming out of that, by the 90s/2000s it was widely decried as being vaguely defined, over-promising and under-delivering. It was a good idea then to ditch the "artificial intelligence" label if you wanted funding. Better to do "machine learning", a more defined field (slash rebrand), focusing (mostly) on approximating functions using large amounts of sample data.
For example, one might feed it 100 000 scans of hand-written digits (from postal codes), and that would result in a function that could tell you whether some scan of a hand-written digit was a 1 or a 2 or any other digit. This was an early application, used to automatically sort letters for the postal service.
The "GenAI" version would be that in reverse, i.e. you tell it draw a 1, and it will generate something that looks like a hand-written 1.
"Deep leaning" just refers to the use of so-called "artificial neural networks", one of these "machine learning" algorithms, which has now taken center stage. The "deep" here refers to the many layers of the "neural net". The word "neural" here is misleading. There is a very superficial similarity between this and biological neurons, as they do differ in pretty much every imaginable way.
Neural nets are used in LLMs, but they are also widely used in e.g. image recognition. So one might call both of them "deep learning". If you wanted to sell a drone that autonomously dive-bombs a tank, that may very well use an "artificial neural net" to identify the tank. But it's not in any way "generative", so you can't call it "GenAI". You could call it "deep learning" or "AI" though, if you were a marketing person.
It actually does not learn from what it's seen before, or at least framing it as such is widely misleading.
These things are fed with ridiculously massive amounts of data during so-called "training", which adjust the weights (parameters) of the model. But that happens when they are created, all the parameters are set in stone afterwards, when the LLM is being used. During use, they do have a (limited in size) context window of tokens (words or rather parts of words, including the chat history) that influence their next output token.
If, for example, the LLM outputs something undesirable (aka "makes a mistake", which the thing has no concept of to begin with), and you chastise it about that, it is likely to promise you to not do that again (apologizing is part of its "training"), which is a false promise, since it cannot guarantee that. Since your complaint is now part of its context window, that may (or may not) actually help it avoid the mistake for a while. But if you reset the the context it will retain nothing, and even if you do not reset it, it will eventually "forget" about it, since it can only retain so many tokens in its context at any one time.
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For posting all the anonymous reactionary bullshit that you can't post anywhere else.
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