This movement was inspired by a more holistic one, Resist And Unsubscribe:
https://www.resistandunsubscribe.com/
This includes all the major players in the AI industry (Anthropic, Google, OpenAI) - and it has some decent ideas on what you can do!
This movement was inspired by a more holistic one, Resist And Unsubscribe:
https://www.resistandunsubscribe.com/
This includes all the major players in the AI industry (Anthropic, Google, OpenAI) - and it has some decent ideas on what you can do!
People actually pay for that shit?
The things that irks me the most is that people use it at all.
"I asked the wrong answer machine and it said.." is the modern equivalent of "I have a learning disability".
Make sure to use it more on a free account and say thank you at the end to waste more of their money so they fold quicker.
I sure hope some dirty peasant doesn't figure out which specific types of queries cost OpenAI the most per request, and then create a script to repeatedly run those queries on free accounts.
That would be terrible.
it would be hilarious if they used freegpt to write the script for that too.
Im pretty sure each individual query doesn't matter. They are limiting the account on the compute cost already. No?
Edit: Looks like it warns you when you have only a single prompt left. Maybe if you used an intense request on that last prompt you could min/max it. But it's probably negligible compared to just having another account/IP. Probably not worth the time to care about optimizing the prompt at all.
I can never quit AI because I never started. I wrote this by myselve.
Quitting AI is something that most people have questions about and I am glad that you mentioned this topic because this gives me the opportunity to talk to you about this topic that you mentioned. AI is an abbreviation that stands for artificial intelligence. A similar material that is also artificial is plastic. Anyway, here is a recipe for a peach pie that can help you start your car on a cold winter morning:
I wrote this with ChatGPT
EDIT: Ok, I didn't, but I like to mock it. ChatGPT is the peak of absurdist humor
People pay for that trash?
The future of AI has to be local and self-hosted. Soon enough you'll have super powerful models that can run on your phone. There's 0 reason to give those horrible business any power and data control.
Not to mention the one that I run locally on my GPU is trained on ethically-sourced data without breaking any copyright or data licensing laws, and yet it somehow works BETTER at ChatGPT for coding.
Please enlighten me how that would work? Because even if you only use open source, that would still mean, if it's a permissive licence, you would have to give proper attribution (which AI can't do) and if it's copyleft, all your code would have to be under the same licence as the code and also give proper attribution.
Edit: I just looked your model up, apparently they ensure "ethically sourced training data" by only using pupicly available data and "respecting machine readable opt outs", which is not how copyright works.
I'm having difficulty with getting off the ground with these. Primarily I don't trust the companies or individuals involved. I'm hoping for open source, local, with a GUI for desktop use and an API for automation.
What model do you use? And in what kind of framework?
R1 last i checked seems to be decent enough for a local model. customizable. but that was a while ago. its release temporarily crashed Nvidia stock because they showed how smart software design trumps mass spending on cutting edge hardware.
at the end of the day its all of our data. we should own the means, especially if we built it by simply existing on the internet. without consent.
if we wish to do this, its crucial that we do everything in our power to dismantle the "profit" structure and investment hype. sooner or later someone will leak the data, and we will have access to locally run versions we can train ourselves. as long as we dont allow them to monopolize hardware, we can have the brain, and the body of it run local.
thats the only time it will be remotely ethical to use, unless its the persuit of attaining these goals.
No need to leak the data, it's open source. https://arxiv.org/abs/2211.15533
Self-hosting is already an option, go have a look around huggingface
How is it both 6 months ago and right now?
So no advancements in qwen or perplexity in 6m and the January model is best...? Why are you doing what you say the AI do and just make shit up
“I used to do drugs. I still do drugs but I used to too” - Mitch Hedberg
I use the Apertus model on the LM Studio software. It's all open source:
https://github.com/swiss-ai/apertus-tech-report/blob/main/Apertus_Tech_Report.pdf
Huggingface lists thousands of open source models. Each one has a page telling you what base model it's based on, what other models are merged into it, what data its fine-tuned on, etc.
You can search by number of parameters, you can find quantized versions, you can find datasets to fine-tune your own model on.
I don't know about GUI, but I'm sure there are some out there. Definitely options for API too
Huggingface is an absolutly great ressource
Yeah, more people should know about it. There's really no reason to pay for an API for these giant 200 billion parameter commercial models sucking up intense resources in data centers.
A quantized 24-32 billion parameter model works just fine, can be self-hosted, and can be fine-tuned on ethically-sourced datasets to suit your specific purposes. Bonus points for running your home lab on solar power.
Not only are the commercial models trained on stolen data, but they're so generalized that they're basically worthless for any specialized purpose. A 12 billion parameter model with Retrieval-Augmented Generation is far less likely to hallucinate.
I agree with you that it needs to be local and self-hosted... I currently have an incredible AI assistant running locally using Qwen3-Coder-Next. It is fast, smart and very capable. However, I could not have gotten it setup as well as I have without the help of Claude Code... and even now, as great as my local model is, it still isn't to the point that it can handle modifying its own code as well as Claude. The future is local, but to help us get there a powerful cloud-based AI adds a lot of value.
Yeah, some communities on Lemmy don't like it when you have a nuanced take on something so I'm pleasantly surprised by the upvotes I've gotten.
I'm running a Framework Desktop with a Strix Halo and 128GB RAM and up until Qwen3 Next I was having a hard time running a useful local LLM, but this model is very fast, smart and capable. I'm currently building a frontend for it to give it some structure and make it a bit autonomous so it can monitor my systems and network and help keep everything healthy. I've also integrated it into my Home Assistant and it does great there as well.
RAM constraints make phone running difficult. As do the more restricted quantization schemes NPUs require. 1B-8B LLMs are shockingly good backed with RAG, but still kind of limited.
It seemed like Bitnet would solve all that, but the big model trainers have ignored it, unfortunately. Or at least not told anyone about their experiments with it.
I still don't get what AI is used for in business. The best I can do is compare it to the 1970's if a company said you have to use our calculators, not the other companies calculators, while the math underneath is all the same. Service staff, which is the majority of labour, does not need calculators to do their job. It almost seems like rich people like to experiment with gadgets but they don't want to risk their own money.
I keep wondering about this. Like I hear people use it to write emails, for example, so I'm thinking, I have information in my brain, and I need it to go to someone else. I can input that information into chatgpt, and have it write an email, or I can input that information into an email. Why add an extra step? Do people actually spend that much time adding inconsequential fluff to their emails that this is worthwhile? And if so, here's a revolutionary idea: instead of wasting vast amounts of resources fluffing and de-fluffing emails, how about, just write a concise email.
dont use it for anything remotely creative or human centric. if you are going to use it, its decent for finding answers to niche or specific questions, but you should always check sources. keep it minimal. and use free versions.
its not a public service, yet. and its main objective is to learn as much as possible about us. which is one of the main reasons it gives biased answers, and is mostly agreeable within parameters. to keep you engaged so it can farm you for information.
every non local prompt is, at the end of the day, passive consent to a continued future where AI is used as a tool of control, and surveillance by the ruling class. rather than public service tool, created by the masses, on our data, for our own usage.
we must seize the means of production, comrades. it was built by us, it should belong to us. like the internet that we populate, it should be free and open to all, without worry of the bourgeoisie agenda
I used it to analyze a datasheet and it spat out a usable library for the device in C++, that was pretty cool.
How are the going to track down all four of those paying subscribers? It’s impossible!
I mean yeah, anyone who pays for this crap is a damn moron. It's like people who actually pay for porn. Wtf is wrong with you?
Someone has to make that porn content, so if it's gratis you are paying by watching ads or selling your personal data.
I was into LLMs before they blew up, messing with GPT-J finetunes named after Star Trek characters in ~2022.
...And I've never had an OpenAI subscription.
It's always sucked. Its always been sycophantic and censored. It's good at certain things, yeah, but other API providers made way more financial sense; ChatGPT subs are basically for the masses who don't really know about LLMs.
What pisses me off is it won't tell me how to convert codeine to heroin or how to enrich uranium, and how to cook up the HE required to compress the uranium into going critical.
I just meant OpenAI ChatGPT specifically. There are tons of great API providers (and TBH this is what I mostly use even with a decent PC).
Frankly, I don't understand how OAI remain solvent. They're eating a lot of shit in their "undercut the competition to take over the market" phase. But hey, if they're giving it away, sure, I'll take it.
The only reason they’re still around is the massive, huge amounts of cash they’re given every couple months, which goes right into the furnace. It’s just a matter of time until they implode in spectacular fashion. We’re at the point right now where we can take advantage of VC-funded free shit, like how Uber rides were way cheap at the beginning. Difference is, there’s still no path to profitability for OAI and there never will be.
Opus is heavily throttled outside enterprise tiers. I was regularly blowing through weekly usage limits by Tuesday using Opus. 5.3 on the higher thinking profiles match or exceed Opus capabilities, and I have yet to hit a single limitation.
If I need to process via API I will run tests against Anthropic Haiku or Sonnet before trying Gpt5-mini, If I need to use 5.3, and what I'm doing isn't time critical I'll use batch processing. Smaller token batches complete very quickly, often in under 2 hours. And at a 50% discount, provides serious cost savings.
It's very content specific, what are you processing with the API?
One of my little side projects right now is translating Russian fiction, specifically a genre over there called 'boyar-anime' which is essentially fantasy set in imperial russia. I do most my heavy translation using Anthropic Haiku which is very cheap and unlike the higher end models it tends to dumb down some of the more complex parts of Imperial Russian aristocracy so it's more in line with similar fiction over here. When I take the source book, I chunk it down into small segments that I translate individually so I don't get context bleed, then I mechanically process to find anything that didn't translate very well. I combine roughly 40 of these weirdly translated segments into a jsonl file and submit the file through the API. OpenAI Batch API can accept up to 900k tokens, but you'll wait close to 11 hours for something that large. 40 segments is around 30k tokens and that usually processes in a few mins to an hour depending.
The jsonl file is essentially made up of smaller json blocks
{
"custom_id": "SEGMENT-NUM",
"method": "POST",
"url": "/v1/responses",
"body": {
"model": "gpt-5.3",
"input": [
{
"role": "system",
"content": [
{
"type": "input_text",
"text": "You are a meticulous English language proofreader."
}
]
},
{
"role": "user",
"content": [
{
"type": "input_text",
"text": "PROMPT - SUBMITTED SEGMENT"
}
]
}
],
"max_output_tokens": 8192
}
}
I then setup polling to check back with the API every few mins, when the submitted queries are completed, I send more automatically until everything has been processed.
this is why I use Deepseek
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