Yeah this is terrible from a security and usability point of view. Just stop using proprietary bs systems. Why do you think so many technical people use Linux and avoid IoT devices like the plague? So we don’t have to deal with companies doing stuff we don’t like without a choice.

Because it’s a lot simpler and avoids the issue of dealing with printer drivers on all your machines.

It’s not an excuse. Socketed RAM has been a bottleneck for iGPUs for a while now.

They kind of did. What other chip allows for 128 GB of VRAM or has that kind of iGPU?

Check your formatting

If right wing (or even other leftist groups) came into an explicitly tankie community and started arguing with people how would you react?

Also do you actually know what tankies are? They aren’t the majority in any country I know of. Non-tankie doesn’t even mean right wing. Anarchists are further left than tankies.

Is this a joke?

Yeah this happened to me too. I guess I made bad choices.

I don’t think partisan is even the right word here as many Lemmy users are too far left for mainstream political parties. In fact I am further left than most any mainstream party, but am still considered a capitalist shill by people here.

I don’t think anti-tankies can be blamed when said tankies regularly engage in brigading of other instances. Like is everyone actually behaved this wouldn’t have been an issue.

Did back propagation even exist in the 60s? That was a pretty fundamental change in what they do.

If we are arguing about really fundamental changes then arguably any neural network is the same and humans are the same as ChatGPT or a mouse, or even something simpler like a single layer perceptron.

There is a lot that can be discussed in a philosophical debate. However, any 8 years old would be able to count how many letters are in a word. LLMs can’t reliably do that by virtue of how they work. This suggests me that it’s not just a model/training difference. Also evolution over million of years improved the “hardware” and the genetic material. Neither of this is compares to computing power or amount of data which is used to train LLMs.

Actually humans have more computing power than is required to run an LLM. You have this backwards. LLMs are comparably a lot more efficient given how little computing power they need to run by comparison. Human brains as a piece of hardware are insanely high performance and energy efficient. I mean they include their own internal combustion engines and maintenance and security crew for fuck’s sake. Give me a human built computer that has that.

Anyway, time will tell. Personally I think it’s possible to reach a general AI eventually, I simply don’t think the LLMs approach is the one leading there.

I agree here. I do think though that LLMs are closer than you think. They do in fact have both attention and working memory, which is a large step forward. The fact they can only process one medium (only text) is a serious limitation though. Presumably a general purpose AI would ideally have the ability to process visual input, auditory input, text, and some other stuff like various sensor types. There are other model types though, some of which take in multi-modal input to make decisions like a self-driving car.

I think a lot of people romanticize what humans are capable of while dismissing what machines can do. Especially with the processing power and efficiency limitations that come with the simple silicon based processors that current machines are made from.

No actually it has changed pretty fundamentally. These aren’t simply a bunch of FCNs put together. Look up what a transformer is, that was one of the major breakthroughs that made modern LLMs possible.

ChatGPT 4o isn’t even the most advanced model, yet I have seen it do things you say it can’t. Maybe work on your prompting.

Exactly this. Things have already changed and are changing as more and more people learn how and where to use these technologies. I have seen even teachers use this stuff who have limited grasp of technology in general.

AGI and ASI are what I am referring to. Of course we don’t actually have that right now, I never claimed we did.

It is hilarious and insulting you trying to “erm actually” me when I literally work in this field doing research on uses of current gen ML/AI models. Go fuck yourself.

If and until the abilities of AI reach the point where they can compensate tech illiteracy and we no longer need to worry about the exorbitant heat production, it shouldn’t be deployed at scale at all, and even then its use needs to be scrutinised, regulated and that regulation is appropriately enforced (which basically requires significant social and political change, so good luck).

Why wouldn’t you deploy that kind of AI at scale?

To be honest I think people keep forgetting that AI strong enough would be smarter than a human, and would probably end up deploying us at scale rather than the other way around. Terminator could one day actually happen. I am not even sure that would be a bad thing given how flawed humans are.

It seems basic logic like this doesn’t actually work on these people. Most really can’t get their heads around the fact that energy costs money and companies want to use less of it wherever possible and practical to do so.

I didn’t realize coal plants were concerned about data centers or AI. TIL.

What? How does that relate to anything I just said?

But in the interest of being slightly less of a dick and responding to what you said even though it’s kinda a non sequitur, companies are only vaguely interested in efficiency.

How is it a non sequitur? If anything the thing you just said makes no sense. Energy is probably the biggest cost these companies have. This I believe is true even for regular data centers and cloud services which is why they always try to use the latest most energy efficient hardware. It’s still not as bad as most anti-AI people seem to believe, mainly because the most energy intensive part happens only once per model (training).

I think it’s more accurate to say that AI is hot for everyone right now so there’s more eyes on it which makes the concept you laid out valid. Where it’s invalid in my experience is that efficiency is just based on “where x executive is paying attention” not an honest attempt to look at return on investment in a rigorous way across the enterprise.

Human labour is expensive. So trying to replace it with AI, even if AI is also expensive, is typically still worth it.

You talk about experience, but I honestly don’t think you have any. Do you actually work in tech? What are your qualifications? Most of the people coming here to complain about this stuff don’t actually have a functional understanding of the thing they are complaining about.

Mainly because energy and data centers are both expensive and companies want to use as little as possible of both - especially on the energy side. OpenAI isn’t exactly profitable. There is a reason companies like Microsoft release smaller models like Phi-2 that can be run on individual devices rather than data centers.