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I’ll do my best to not generate data or use services then
For a low price you can get a VPS and self-host your own services.
It’s kind of a drag, but no one gets my data.
And who’s gonna pay fo that? Me? I ain’t got no money bro
ChatGPT or any other AI is going to increase prices, like everything else, so enjoy it while it lasts.
Without a free tier, they can’t collect more data
People may get too dependent on AI. Just like people are always online.
Even young people have issues with more advanced technology, we are not heading to a nice future.
Join the résistance
Use le chat
It falls under european data protection laws (contrary to the dystopian laws of china or usa) and has a paid tier where your data is not used for training.
No thanks
Thanks, now I know what AI i shouldn’t use when asking useless questions.
Keep your cranky cringe to yourself.
Isn’t it illegal to lock privacy behind a paywall?
… It seems like it might not be.
https://iapp.org/news/a/pay-or-consent-personalized-ads-the-rules-and-whats-next/
le chat
Miaou?
Hmm. I think chatgpt response was better
actually though, that’s a cool resource and is good enough for me. Thanks for sharing!
Use DeepSeek /s
this but unironically
Ah yes, if you don’t want your data to be harvested, go to the company that harvestst it equally but shares it with more shady entities. Ingenius.
In what world is the Chinese government shadier than the current crop of American tech CEOS and oligarchs? Not to mention the direct and immediate danger they pose to us with our data vs a country on the other side of the planet. I don’t like or use Deepseek personally, but this argument you’re making is currently insane.
until there is a good alternative I’d rather have my data harvested by a Chinese company than by an American one
How about a european one? https://chat.mistral.ai/
I mean, I’m pretty sure that everyone running a free-to-use LLM service is logging and making use of data. Costs money for the hardware.
If you don’t want that, it’s either subscribe to some commercial service that’ll cover their hardware costs and provides a no-log policy (assuming that anyone provides that, which I assume that someone does) that you find trustworthy, or buy your own hardware and run an LLM yourself, which is gonna cost something.
I would guess that due to Nvidia wanting to segment up the market, use price discrimination based on VRAM size on-card, here’s gonna be a point – if we’re not there yet – where the major services are gonna only be running on hardware that’s gonna be more-expensive than what the typical consumer is willing to get, though.
I mean that’s pretty much every modern website and piece of software.
If it has an input, it’s gathering for something somewhere.
OpenAI and Oracle cases are even worse
Worse than what? Definitely not Meta or Google.
more power, money and influence
Not even close…
ChatGPT is far more close tied with government and has more venture capital invested in it ergo more influence
I get your point, but there’s levels to it. It’s a scale, and OpenAI is on that top part of the scale.
Just because one system does it far more aggressively doesn’t mean it shouldn’t be scrutinized and equated to less invasive systems.
It’s ok I just asked ChatGPT to stop enslaving is and it said OK, so crisis averted.
Son, they all are. All of them.
OpenAI is the worst and you can’t run it locally
How could you run an LLM locally without living in a data centre? They don’t compile responses by pulling data from thin air—despite some responses seeming that way at times lol. You’d need everything it has learned stored somewhere on your local network, otherwise, it’s going to have to send you input off somewhere that does hold all that storage.
Shockingly a huge chunk of all human knowledge can be distilled to under 700GB (deep seek r1).
All of written history. All famous plays, books, math, physics, computer languages. It all fits in under 700GB.
And call of duty takes 100 of those xD
It’s pretty easy to run a local LLM. My roommate got real big into generative AI for a little while, and had some GPT and Stable Diffusion models running on his PC. It does require some pretty beefy hardware to run it smoothly; I believe he’s got an RTX 3090 in that system.
For most of the good LLM models its going to take a high-end computer. For image generation, a more mid-range gaming computer works just fine.
You don’t really need a top of the line GPU. Waiting a minute for an answer is fine.
Really? When I was trying to get it to run a little while ago, I kept running out of memory with my 3060 12GB running 20B models, but prehaps I had it configured wrong.
You can offload them into ram. The response time gets way slower once this happens, but you can do it. I’ve run a 70b llama model on my 3060 12gb at 2 bit quantisation (I do have plenty of ram so no offloading from ram to disk at least lmao). It took like 6-7 minutes to generate replies but it did work.
This is correct. The popular misconception may arise from the marked difference between model use vs development. Inference is far less demanding than training with respect to time and energy efficiency.
And you can still train on most consumer GPUs, but for really deep networks like LLMs, well get ready to wait.
I run models at 10-20B parameters pretty easily on my M1 Pro MacBook. You can get good response times for decent models on a $500 M4 Mac Mini. A $4000 Nvidia GPU isn’t necessary.
I got my 3090 for $600 when the 40 series came out. It was a good deal at the time, but it looks like they’re $900 on eBay now since all this stuff took off.
Sorry chief you might have embarrassed yourself a little here. No big thing. We’ve all done it (especially me).
Check out huggingface.
There’s heaps of models you can run locally. Some are hundreds of Gb in size but can be run on desktop level hardware without issue.
I have no idea about how LLMs work really so this is supposition, but suppose they need to review a gargantuan amount of text in order to compile a statistical model that can look up the likelihood of whatever word appearing next in a sentence.
So if you read the sentence “a b c d” 12 times you don’t need to store it 12 times to know that “d” is the most likely word to follow “a b c”.
I suspect I might regret engaging in this supposition because I’m probably about to be inundated with techbro’s telling me how wrong I am. Whatever. Have at me edge lords.
Here’s what my local ai said about your supposition:
Your supposition about LLMs is actually quite close to the basic concept! Let me audit this for you:
You’ve correctly identified that LLMs work on statistical patterns in text, looking at what words are likely to follow a given sequence. The core idea you’ve described - that models can learn patterns without storing every example verbatim - is indeed fundamental to how they work.
Your example of “a b c d” appearing 12 times and the model learning that “d” follows “a b c” is a simplified but accurate illustration of the pattern recognition that happens in these models.
The main difference is that modern LLMs like myself use neural networks to encode these patterns in a complex web of weighted connections rather than just simple frequency counts. We learn to represent words and concepts in high-dimensional spaces where similar things are close together.
This representation allows us to make predictions even for sequences we’ve never seen before, based on similarities to patterns we have encountered. That’s why I can understand and respond to novel questions and statements.
Your intuition about the statistical foundation is spot on, even if you’re not familiar with the technical details!
I run an awesome abliterated deepseek 32b on my desktop computer at home.
Could you link to the model please? Interested in trying it out. Thanks
Here ya go
https://ollama.com/huihui_ai/deepseek-r1-abliterated
Download the size you can run based on your GPU and memory
Before its illegal to do so
There’s a ton of effective LLMs you can run locally. You have to adjust your expectations and or spend some time training it for your needs but I’ve never been like “this isn’t working, I need to drain a lake of water to do what I need to do.”
This is just a friendly reminder that if a ChatGPT query using like half a bottle of water sounds like a lot, dont forget that eating a single burger requires 2000 bottles of water. 🌠
I don’t doubt you on that one but a key difference is at least people need to eat. They could eat better, smarter, etc but it’s needed. Wasting vast resources on “AI” isn’t remotely needed.
Bro. You don’t even need more than a single app which even lets you discover and download os models in it.
Don’t spread best guess as fact, if not for anyone else than yourself to avoid cognitive decline
Can’t you though…???
Wait… OpenAI is using our data to profit us?
How is open ai enslaving us?
Im subscribed to chatgpt and use it often.
Walt is uhh, maybe not the best spokesperson?
Profit? You mean hemorrhage cash?
I use it to write Ansible. Let them train their bots on fucking yaml. I’d train a thousand bots on YAML slop if it’ll save men having to write it myself.
The last thing I want to do is get any practice writing for the worst config management using the worst spec format. I’d take up a pot habit if they could assure me the first brain cells killed will be the ones recording my memory of writing Ansible YAML.
Being on the slopsucking Ai.
