“The surveillance, theft and death machine recommends more surveillance to balance out the death.”
I kind of assumed it worked like this before anyway. Good reason to use local models.
Sadly, Local models arent there yet. I have tech nerds in my company spending $3-10k building their own systems and they’re still not getting the speeds and quality that these subscriptions have.
$3-10k…not getting the speeds and quality
I mean, that’s true. But the hardware that OpenAI is using costs more than that per pop.
The big factor in the room is that unless the tech nerds you mention are using the hardware for something that requires keeping the hardware under constant load — which occasionally interacting with a chatbot isn’t going to do — it’s probably going to be cheaper to share the hardware with others, because it’ll keep the (quite expensive) hardware at a higher utilization rate.
I’m also willing to believe that there is some potential for technical improvement. I haven’t been closely following the field, but one thing that I’ll bet is likely technically possible — if people aren’t banging on it already — is redesigning how LLMs work such that they don’t need to be fully loaded into VRAM at any one time.
Right now, the major limiting factor is the amount of VRAM available on consumer hardware. Models get fully loaded onto a card. That makes for nice, predictable computation times on a query, but it’s the equivalent of…oh, having video games limited by needing to load an entire world onto the GPU’s memory. I would bet that there are very substantial inefficiencies there.
The largest GPU you’re going to get is something like 24GB, and some workloads can be split that across multiple cards to make use of VRAM on multiple cards.
You can partially mitigate that with something like a 128GB Ryzen AI Max 395+ processor-based system. But you’re still not going to be able to stuff the largest models into even that.
My guess is that it is probably possible to segment sets of neural net edge weightings into “chunks” that have a likelihood to not concurrently be important, and then keep not-important chunks not loaded, and not run non-loaded chunks. One would need to have a mechanism to identify when they likely do become important, and swap chunks out. That will make query times less-predictable, but also probably a lot more memory-efficient.
IIRC from my brief skim, they do have specialized sub-neural-networks, which are called “MoE”, for “Mixture of Experts”. It might be possible to unload some of those, though one is going to need more logic to decide when to include and exclude them, and probably existing systems are not optimal for these:
kagis
Yeah, sounds like it:
https://arxiv.org/html/2502.05370v1
fMoE: Fine-Grained Expert Offloading for Large Mixture-of-Experts Serving
Despite the computational efficiency, MoE models exhibit substantial memory inefficiency during the serving phase. Though certain model parameters remain inactive during inference, they must still reside in GPU memory to allow for potential future activation. Expert offloading [54, 47, 16, 4] has emerged as a promising strategy to address this issue, which predicts inactive experts and transfers them to CPU memory while retaining only the necessary experts in GPU memory, reducing the overall model memory footprint.
Naturally the commercial systems are going to be strictly better, but the best models I can run on my 3090 have been good enough for me for a couple years now, and have massively improved over that time. Currently mostly use qwen3-coder which is really solid. It just feels so much nicer to use knowing it’s private and not being datamined for who knows what,
i’m running 2x 3060 (12gb cards, vram matters more than clockspeed usually) and if you have the patience to run them the 30b qwen models are honestly pretty decent; if you have the ability and data to fine-tune or LORA them to the task you’re doing, it can sometimes exceed zero shot performance from SOTA subscription models.
the real performance gains come from agentifying the language model. With access to wikipedia, arxiv, and a rolling embedding database of prior conversations, the quality of the output shoots way up.
agentifying the language model
Any recommendations on setups for this?
If the user is a Nazi it probably auto sends their resume to ICE
So it is not stupid enough to just use it, some people are so totally stupid and think what they put into a commercial, online thing would be private.
I don’t actually have a problem with this. If people are stupid enough to admit to a crime or engage in criminal activity on a platform that they don’t control, that’s on them. I put this as the next step of evolution from people who would commit a crime on youtube for views then get shocked pikachu’d when the police arrest them for it. They have no one to blame but themselves, they brought a 3rd party AI company into it and they did not consent to be an accomplice and if there is any company out there with the resources to have AI scan conversations to flags to send to the police with good accuracy, openAi would definitely be at the front of it.
Ahh, the ol’ ‘nothing to hide’ defense.
Ever consider things that are labeled as ‘crimes’ can and will be anything the people in power want?
Just because, say, calling Republicans ‘shithead pedophiles’ on Lemmy isn’t illegal now doesn’t mean Cheeto Mussolini won’t make it illegal tomorrow.
You’re fine with invasion of privacy as long as it only affects criminals.
I think you’ll find that once privacy is broken you’d be surprised how many people end up under that umbrella.
Using the fucking GPT is the privacy invasion.
So yes, once the company has the logs and detects any criminal or dangerous activity, it should report it.
Stop using chatbots in the first place.
Can we have it affect the oligarchs and authoritarian fascists, too?
Bro wants to comply ahead of time. lol You’re a weird little fool
Well, you should have a problem with it but not for the reasons you think. Any invasion of privacy is an issue when the people in control get to decide what is a reportable offense without explicitly telling you. I get it, you definitely shouldn’t be admitting anything illegal or asking illegal advice from a chat bot. You shouldn’t be doing anything that is illegal in the first place.That’s basically the same as googling how to make a bomb and if you’re that dumb you’ll get what’s coming to you. The issue arrives when you look at the bigger picture. If they have the ability to report anything they want to the police, what’s stopping them from releasing anything they want to anyone they want at any time? And when it comes to those receiving the data that’s been reported, what proof do you have that these entities have yours or anyone else’s interests or safety in mind? What if they decide to change the rules on what they should report, they don’t tell you, and then retroactively flag a bunch of your conversions with said LLM.
It’s the same kinda situation that we face with these AI cameras that track us and our vehicles literally everywhere we go. There have already been multiple cases where people in law enforcement were using these tools to stalk people like ex girlfriends. All this is putting a lot of trust into people that none of us even know and expect them to have the best of intentions. What would stop them from reporting that you asked ChatGPT about the current situation in Gaza?
Fair points.
One thing I think we all miss: what happens when an overzealous government makes something a crime retroactively? Say, um, disparaging two Cheetos in an ill fitting suit masquerading as a world leader.
That’s part of why we should care about privacy and why we should care when data we expect to be private isn’t.
Most tech users are victims in a system they don’t understand. We might complain that they don’t want to understand but the truth is the providers don’t want them to understand - as it’s easier to sell them whatever crap they’re shilling.
Being criminally stupid when planning crimes is pretty stupid.
I kinda agree. While I do want these llm companies to be more private, in terms of data retention, I think it’s native to say that a company which is selling artificial intelligence to hundreds of millions of users should be totally ambivalent in the face of llm induced psychosis and suicide. Especially when the technology only gets more hazardous as it becomes more capable.
As much as I hate the AI-gens, this is probably a good thing after that poor kid got talked into killing himself. I assume Google et al do similar already.
Now, if the cops react to being called for a person in crisis by tazing somebody, that’s a different problem.
they will find out about my relation with uwu chatgpt mechahitler skibidi sigma wifu
This is why i keep my chat gpt under the sofa so when buckling up for safety my open ai stays extra crunk.
There is no privacy if you don’t self-host everything.
Ironically you can use it without logging on, so the people hurt the most are the paid users that are voluntarily giving money to the company.
On-site self- hosting, on owned hardware. Who knows what’s going on behind the closed doors of data centers around the world.
And let’s not get into industry standard
hardware backdoorsremote control systems.
Did they think there was patient-sycophantBot privilege or something?
What a snitch, grok is this real??
“Yes, Nazis are cool.” -Grok, probably
Stupid is, etc