• 5 Posts
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Joined 1 year ago
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Cake day: August 11th, 2023

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  • I’ve tried making this argument before and people never seem to agree. I think Google claims their Kubernetes is actually more secure than traditional VMs, but how true that really is I have no idea. Unfortunately though there are already things we depend upon for security that are probably less secure than most container platforms, like ordinary unix permissions or technologies like AppArmour and SELinux.





  • That’s not true though. The models themselves are hella intensive to train. We already have open source programs to run LLMs at home, but they are limited to smaller open-weights models. Having a full ChatGPT model that can be run by any service provider or home server enthusiast would be a boon. It would certainly make my research more effective.


  • 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.






  • 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.



  • 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.







  • areyouevenreal@lemm.eetolinuxmemes@lemmy.worldWindows VS Linux
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    2 months ago

    Yeah it’s not always that simple. You haven’t been around long enough to see the stuff that can go wrong with installing Windows. For example I recently had Windows refuse to see both SSDs in a machine. All because of something called Intel VMD. Took me a handful of attempts before I found the problem.

    When Windows installs work they are fairly simple if long, but when they don’t work oh boy.

    The unplugging of internet to get a local account?

    Also they disabled that for Windows Home.

    Some Lemmy users are actually just wankers. I would like it if you all stopped. It’s especially great when I have people like you who probably aren’t even experienced in tech.