Ken Cheng is a great satirist and probably knows thats not how it works anymore. Most model makers stopped feeding random internet user garbage into training data years ago and instead started using collections of synthetic training data + hiring freelance ‘trainers’ for training data and RLHF.

Oh dont worry your comments are still getting scraped by the usual data collection groups for the usual ad selling and big brother bs. But these shitty AI poisoning ideas I see floating around on lemmy practically achieve little more than feel good circle jerking by people who dont really understand the science of machine learning models or the realities of their training data/usage in 2025. The only thing these poor people are poisoning is their own neural networks from hyper focusing defiance and rage on a new technology they can’t stop or change in any meaningful way. Not that I blame them really tech bros and business runners are insufferable greedy pricks who have no respect for the humanities who think a computer generating an image is the same as human made art. Also its bs that big companies like meta/openAI got away with violating copyright protections to train their models without even a slap on the wrist. Thank goodness theres now global competition and models made from completely public domain data.

Which ones are not actively spending an amount of money that scales directly with the number of users?

Most of these companies offer direct web/api access to their own cloud supercomputer datacenter, and All cloud services have some scaling with operation cost. The more users connect and use computer, the better hardware, processing power, and data connection needed to process all the users. Probably the smaller fine tuners like Nous Research that take a pre-cooked and open-licensed model, tweak it with their own dataset, then sell the cloud access at a profit with minimal operating cost, will do best with the scaling. They are also way way cheaper than big model access cost probably for similar reasons. Mistral and deepseek do things to optimize their models for better compute power efficency so they can afford to be cheaper on access.

OpenAI, claude, and google, are very expensive compared to competition and probably still operate at a loss considering compute cost to train the model + cost to maintain web/api hosting cloud datacenters. Its important to note that immediate profit is only one factor here. Many big well financed companies will happily eat the L on operating cost and electrical usage as long as they feel they can solidify their presence in the growing market early on to be a potential monopoly in the coming decades. Control, (social) power, lasting influence, data collection. These are some of the other valuable currencies corporations and governments recognize that they will exchange monetary currency for.

but its treated as the equivalent of electricity and its not

I assume you mean in a tech progression kind of way. A better comparison might be is that its being treated closer to the invention of transistors and computers. Before we could only do information processing with the cold hard certainty of logical bit calculations. We got by quite a while just cooking fancy logical programs to process inputs and outputs. Data communication, vector graphics and digital audio, cryptography, the internet, just about everything today is thanks to the humble transistor and logical gate, and the clever brains that assemble them into functioning tools.

Machine learning models are based on neuron brain structures and biological activation trigger pattern encoding layers. We have found both a way to train trillions of transtistors simulate the basic information pattern organizing systems living beings use, and a point in time which its technialy possible to have the compute available needed to do so. The perceptron was discovered in the 1940s. It took almost a century for computers and ML to catch up to the point of putting theory to practice. We couldn’t create artificial computer brain structures and integrate them into consumer hardware 10 years ago, the only player then was google with their billion dollar datacenter and alphago/deepmind.

Its exciting new toy that people think can either improve their daily life or make them money, so people get carried away and over promise with hype and cram it into everything especially the stuff it makes no sense being in. Thats human nature for you. Only the future will tell whether this new way of precessing information will live up to the expectations of techbros and academics.

Theres more than just chatgpt and American data center/llm companies. Theres openAI, google and meta (american), mistral (French), alibaba and deepseek (china). Many more smaller companies that either make their own models or further finetune specialized models from the big ones. Its global competition, all of them occasionally releasing open weights models of different sizes for you to run your own on home consumer computer hardware. Dont like big models from American megacorps that were trained on stolen copyright infringed information? Use ones trained completely on open public domain information.

Your phone can run a 1-4b model, your laptop 4-8b, your desktop with a GPU 12-32b. No data is sent to servers when you self-host. This is also relevant for companies that data kept in house.

Like it or not machine learning models are here to stay. Two big points. One, you can self host open weights models trained on completely public domain knowledge or your own private datasets already. Two, It actually does provide useful functions to home users beyond being a chatbot. People have used machine learning models to make music, generate images/video, integrate home automation like lighting control with tool calling, see images for details including document scanning, boilerplate basic code logic, check for semantic mistakes that regular spell check wont pick up on. In business ‘agenic tool calling’ to integrate models as secretaries is popular. Nft and crypto are truly worthless in practice for anything but grifting with pump n dump and baseless speculative asset gambling. AI can at least make an attempt at a task you give it and either generally succeed or fail at it.

Models around 24-32b range in high quant are reasonably capable of basic information processing task and generally accurate domain knowledge. You can’t treat it like a fact source because theres always a small statistical chance of it being wrong but its OK starting point for researching like Wikipedia.

My local colleges are researching multimodal llms recognizing the subtle patterns in billions of cancer cell photos to possibly help doctors better screen patients. I would love a vision model trained on public domain botany pictures that helps recognize poisonous or invasive plants.

The problem is that theres too much energy being spent training them. It takes a lot of energy in compute power to cook a model and further refine it. Its important for researchers to find more efficent ways to make them. Deepseek did this, they found a way to cook their models with way less energy and compute which is part of why that was exciting. Hopefully this energy can also come more from renewable instead of burning fuel.

Lowtechmagazine wrote an excellent article about decadent mist showers that use many small nozzles spraying very fine mist particle sizes water on you as a much more efficient way to use water for showers. I would love to install and try out something like that one day.

Okay I think the term ‘foot-gun’ is supposed to evoke the image of someone loading a gun and pointing it at their own foot. I can’t help trying to picture a gun thats operated by a foot. Like a mech suit with a robot leg that also fires massive tank shattering shells when you do a roundhouse kick as a human operator. Or a veteran prosthetic leg that’s also a rifle when you kick it the right way.

The brain rot seeps just a little bit more every time I see the term ‘foot-gun’ please help.

I dont really understand the whole lemmysilver thing but thanks for getting a fun community charity raffle set up. You didn’t need to get a prize pool together so going the extra mile out of pocket to do that for a community event is such a cool move.

I don’t care what PR rep says, its cost cutting one way or another. I hypothesize that gorilla glass had a 10 year contract with the phone manufactures and now that the contract is up some are choosing to cut out the moddle man in hopes of cheaper in-house solutions.

The number pad only ever became relevant to me after decades when I began playing video games that have more keybindings than I have brain cells. Caves Of Qud makes use of basically the the whole number pad just to manually move in 8 different directions.

Some people need something to rage and virtue signal against. Those who work in private STEM sectors or took machine learning classes years before the LLM craze already understand the tool is here and are willing to learn to work with it if applicable in their job or daily life.

Those who don’t understand anything about the science of machine learning and are angry at the how megacorporations got away with unconsentually scraping their copyright infringed data off the internet for the first iterations of training data still get to let off some steam by calling it ‘hyped autocomplete just as bad as NFTs that will never do what a person can’.

If I were an artsy type whos first exposure to ML was having my work stolen followed by the thief bragging to my face about how copy protection laws dont matter to the powerful and now they can basically copy my honed style 1 to 1 with a computer to sell as an product, I would be unreasonably pissed too and not interested this whole 'AI’thing. Megacorps made chatGPT and stable diffusion using my work therefore AI bad. I get it.

That said, I’m not an artsy type or an idealist. I’m a practical engineer who builds systems to process the flows of information and energy with the tools available at my dispersal. Theres more to machine learning than proprietary models made with stolen information to be sold to th masses. Instead models are just the next new way to process large datasets full of complicated information. Its just that now were taking cues from natures biological information processing systems. Whether such processes prove more certain and effective to the old analog and digital ways have yet to be seen. Perhaps using these new tools will open up entirely different ways of treating information for all of society. Perhaps it will be just another niche thing for researchers to write papers about. Time will tell.

The inefficacy of current public education system is a feature not a bug. The rulers want workers just smart enough to measure inches and run the machines to keep the money printers flowing. But not smart enough to realize just how badly they’re getting fucked over by a system that sold out and threw them overboard before they were even born. You need high level language and a general understanding of history to comprehend high level abstractions that govern human hierarchy. Ill bet 5$ on which subjects are getting most cuts in public schools.

I was going to say it sounds like linux mint would be your dream OS its stable and bullet proof. Download everything through package manager if you really need up to date program flatpaks or appimages have you covered. Never have the computer force an update on you or change things around again. Both my elderly parents use LM every day for years not one complaint after I set everything up for them with like web app shortcuts to banks and stuff. I think youll like it, modern linux is so much better than years ago its unreal. Look for a cheap used thinkpad if you a laptop user.

relevant

In the winter my home can go down into the 40F-50F range with all available heating running on full. Even with electric blankets its better to layer up with thermal underwear, hats, coats, three layers of pants, and gloves.

My mom says she can’t stand a bunch of fabric on her which I guess is fair. I personally can’t stand freezing to death while I sleep myself so its a fair trade.

> kaiju demon cleaves Tampa
> prehistoric kaiju sized mega-crocodile erupts from crack in ground
> they battle it out, croczilla wins by continuous death rolling 
> "Oh I must have switched on the sci-fy channel by accident"
> mfw its national news station with live coverage

Twitter: “lmao this new retcon of Godzilla is wild”

So, what’s your codeword for pot and where does the bud grow season fit in? Hope it all works out :)

Voxelibre does have sprint, its ‘aux_1’ in the settings. Left Ctrl by default I think?

I’m not sure the smaller Lemmy servers running on a pi or resident internet upload could handle the equal sizable fraction of .world . it would be interesting to calculate how many users total on Lemmy divided by how many public joinable instances and see the averages or which servers are forced to scale the most.

This would take away complete user freedom to choose the server they want which is controversial.

FromSoft fans who have been around since Kingfield in the late 90s: “always has been” (because from hit gold with the old and decaying fantasy world with dwindling hope in its inhabitants atmospheric vibe and keep reusing it)

I did not spin it myself, though it sounds like a fun thing to try!

Before picking up crochet I was already a big fan of hemp. I’m a pot smoker first and foremost so thats where the interest stems from. I vaporize the plant for medicine, might as well see if I can wear its fibers too.

As I learned more about industrial hemp and its many pros as a natural fiber material, I became more interested from an ideological and material consumer perspective.

Hemp is stronger than steel in tensile strength, so anything you make with it is incredibly resistant to wear. Its a material that wears in like denim jeans so its fantastic for bedding sheets and clothing in the long term as it smooths and softens. This is incredibly appealing to me as a material property. I got so sick of all my cheap textile things from a store wearing down so its refreshing to make something with durability by my own hand as a “fuck it I’ll do it myself”. The hand towels are never going to seriously fray or come undone or turn rough and thinned out through normal wear.

I don’t like plastic fibers either. A lot of crochet yarn is either acrylic or a blend of acrylic and natural. I don’t want to introduce any more microplastics into my enviroment.

Hemp is a replenishing crop that heals the soil, puts nutrients in, captures a shit load of Co2, and grows like a weed without need for lots of water or fertilizer. compared to cotton which depletes soil, drinks water like crazy, and needs constant fertilizer. By buying hemp I’m voting with my wallet and saying I want to support ecologically friendly sources of my textiles which is a feel good kind of thing.

Hemp isnt a perfect material, though. Remember how I said its tough like steel? Its a real bitch to work with when trying to get a loop inside another loop in crochet. Absolutely no give at all which made it a real pain when the tolerances werent quite right. Lots of undoing and redoing the same loops. I imagine acrylic is much more workable and forgiving when trying to force it through.

Its also not a plush soft velvety texture. Its a rough and tough type of fiber that needs to get worn in before its really enjoyable to touch or use as a body scrub.

Sorry about the infodump, hope this helps you understand my reasoning.

This reply chain is only one degree of separation away from a full blown Terrence McKenna Timewave Zero situation