• Fallibilist@feddit.uk
    link
    fedilink
    English
    arrow-up
    17
    arrow-down
    2
    ·
    3 days ago

    Anthropic has committed to spending at least $518 billion over a decade on cloud services, computing and infrastructure.

    They’re betting everything on AGI. I don’t think anyone there at any point has even hoped that the tiny initial revenue streams would cover the absolutely gigantic upfront costs of setting everything up.

    Now, whether they’ll actually reach AGI before this thing implodes is anyone’s guess. The people who claim that they absolutely will are full of shit just like the ones claiming they absolutely will not. Nobody knows and only time will tell.

    • BrainBow65@lemmy.world
      link
      fedilink
      English
      arrow-up
      46
      ·
      3 days ago

      I’m just going to throw in my 2 cents on the AGI issue since I have a better understanding than average. I’m currently a computational neuroscience PhD student. I don’t work in theoretical neuroscience currently but that’s my hope after I finish my doctorate.

      I don’t believe current transformer architectures are capable of AGI and all big AI companies just seem to be adding more parameters to established transformer architectures.

      Tap for spoiler

      From what I understand transformer architectures act similarly to primary sensory cortices, they model complex probability densities. These companies appear to be banking on the idea that adding more training data, having smaller networks working together with different expertise, and having the train of thought (phonological loop) modeled as part of the PDF is enough to reach AGI. I disagree.

      While all of those things are interesting solutions to parts of the problem I don’t think they address some of the bigger issues.

      1. in biological intelligence memory recall is built into the same system as information processing. Associations between things are learned by simultaneously recalling and processing
      2. decision making and higher order processing do not fit into a transformer architecture
      3. temporal encodings are only made, in the transformer system, via the attention mechanism which is much less efficient than a more biological mechanism.
      • Fallibilist@feddit.uk
        link
        fedilink
        English
        arrow-up
        7
        ·
        3 days ago

        That’s perfectly reasonable. I mostly take issue with the people claiming absolute certainty either way.

      • PalmTreeIsBestTree@lemmy.world
        link
        fedilink
        English
        arrow-up
        2
        ·
        3 days ago

        Haven’t there been developments in biological computers recently? Wouldn’t that be the key to AGI? I am a total idiot so I know zero about what you are doing or talking about. It just makes more sense for a computer to think like us if it has the same hardware as us is how I see it.

        • BrainBow65@lemmy.world
          link
          fedilink
          English
          arrow-up
          8
          ·
          3 days ago

          There are positives and negatives to using cells for computing. There are very complex systems that are responsible for making sure cells grow in the correct architecture and are supported property via blood vessels and glial cells. There is also definitely something to be said about glial cells themselves having a role in computation (whole other topic I won’t get into) not just neurons.

          If were just looking at the input output relationship with neurons we can model it pretty well using neuromorphic hardware which is designed to respond like a neuron. There are still gaps but and there are scientists who believe it isn’t close enough.

          Our current hardware can model neurons closely as well but its less efficient at it. The current AI models use point neurons which takes a lot less computing power but I don’t think they’re the way to AGI. Personally I’m a fan of the adaptive exponential leaky integrate and fire model or the spike response model

      • postscarce@lemmy.dbzer0.com
        link
        fedilink
        English
        arrow-up
        2
        ·
        3 days ago

        This is really interesting. Do you know of anywhere that I could read more about comparing neuronal function to transformer architecture?

        • BrainBow65@lemmy.world
          link
          fedilink
          English
          arrow-up
          6
          arrow-down
          1
          ·
          3 days ago

          Good question! Unfortunately, I haven’t found a good source myself. I’ve been trying to piece it together based on my theoretical/mathematical neuroscience background and self-study about transformer architectures. The problem is the point neurons in transformers don’t map to neurons in cortex. You have to instead look at the bigger functions that are being computed by each system.

          The best single source to learn more about theoretical neuroscience is Neuronal Dynamics: From Single Neurons to Networks and Models of cognition. But its super math heavy. If you want to easier to digest videos I recommend Artem Kirsanov on youtube. For transformer architecture 3 Blue 1 Brown has a great series of videos about it on YouTube as well.

      • Regrettable_incident@lemmy.world
        link
        fedilink
        English
        arrow-up
        3
        arrow-down
        2
        ·
        3 days ago

        I kinda feel like actual AI will not be made by humans, but by a model that is able to reprogram and upgrade itself until it has some sort of agency. That said, my experience in the field is from the 90s so I really know fuck all that’s relevant today.

        • Fallibilist@feddit.uk
          link
          fedilink
          English
          arrow-up
          7
          ·
          3 days ago

          Generally the benchmark for AGI has been “human level intelligence” meaning that from there on AI is also the best AI researcher and human input is no longer needed in developing it. That’s where the concept of singularity or intelligence explosion stems from.

          The narrative here tends to be that it goes from AGI to ASI (Artificial Super Intelligence) very rapidly but in my view there’s not a significant difference between the two. AI that is as intelligent as a human but not more would still process information about a million times faster so effectively it would still be superintelligent.

          • joonazan@discuss.tchncs.de
            link
            fedilink
            English
            arrow-up
            1
            ·
            3 days ago

            I disagree on the speed. The “human level intelligence” would be about as fast as a human on tasks. It might do them very differently, so it could be superhumanly fast at some things like reading a whole book.

            The thing that I doubt is that this would create the prophecised feedback loop. Sure, the AI could be a bit better than a human at further developing itself but it is probably also really hard to increase the intelligence.

            One thing that can’t be denied is that AGI could be taught once and then cloned instead of all the work that goes into training humans.

          • Regrettable_incident@lemmy.world
            link
            fedilink
            English
            arrow-up
            2
            ·
            3 days ago

            That makes sense. That said, I’m not sure superintelligence is just a matter of processing speed. It’s an interesting question - give me a complex problem and say a thousand years to work on it. I kinda feel there’s some problems I’m just not equipped to solve, no matter how much processing time I have. But of course, that’s impossible to test. And in computer terms, you could copy a whole team of me to work together. Hmm.

            Yeah, I concur that the difference between AGI and ASI is likely moot. If an intelligent machine is able to upgrade itself to be more intelligent - well, I think we’d all do that if we could! I’m not sure that more intelligence and faster processing are the same thing, but I’m also not sure that we could distinguish between the two in practical terms.

    • NonconfrontationaI@lemmy.ml
      link
      fedilink
      English
      arrow-up
      13
      arrow-down
      4
      ·
      3 days ago

      Plus I mean what good can an AGI do for me? I’m still not interested in the slightest in paying someone to atrophy my brain.

      • Kurtismayfield@lemmy.zip
        link
        fedilink
        English
        arrow-up
        10
        ·
        3 days ago

        Oh, AGI isn’t for you. Its for the AI cultists to worship once they summon it. The AI cultists think they can control thier god, even thought it will be integrated into everything if it is truly super intelligent. Then they will realize that they didn’t learn from all of the dystopia Sci fi warning them about summoning their god.

        Either that, or its all marketing bullshit.

      • Corkyskog@sh.itjust.works
        link
        fedilink
        English
        arrow-up
        2
        ·
        edit-2
        3 days ago

        AGI isn’t for us, it’s to replace us. AGI is the pipedream they have been selling of actually reducing your workforce by offloading it all onto AGI agents. They either don’t reach AGI before their debt obligations come due in 2027 causing the bubble to burst and causing the next great recession or the achieve AGI before that happens and everyone slowly loses their jobs causing the next great recession.

          • Corkyskog@sh.itjust.works
            link
            fedilink
            English
            arrow-up
            2
            ·
            3 days ago

            Yeah, I think they forgot about competition or assumed they wouldn’t have it by the time it matters.

            It only works if they stop training new models and can actually follow their 6 year depreciation schedule on their GPUs. But that would make Jensen Huang cry, and they do have competition right now. You can’t put a bunch of effort into creating one AGI model because then a few months later OpenAI or Anthropic releases a slightly better model and all your contracts go away next year.

      • five_bucks@lemmy.ca
        link
        fedilink
        English
        arrow-up
        2
        arrow-down
        5
        ·
        3 days ago

        Brain atrophy is only a risk if you don’t reallocate the time saved by applying AGI to an issue you would otherwise have to figure out yourself.

        Use it on problems you can’t bear to manage and not on something for which you have a passion.

        It could be incredible if society doesn’t collapse.

        • NonconfrontationaI@lemmy.ml
          link
          fedilink
          English
          arrow-up
          6
          arrow-down
          1
          ·
          3 days ago

          The problems I can’t bear to manage are not manageable by a chat bot, lol.

          Plus with the incoming climate apocalypse, I’d rather be more self reliant and not less.

      • Uplink@programming.dev
        link
        fedilink
        English
        arrow-up
        4
        arrow-down
        9
        ·
        3 days ago

        Now, whether they’ll actually reach AGI before this thing implodes is anyone’s guess.

        I’m with you but in a professional environment, there is simply no way around AI anymore. It’s too good to not use unfortunately.

        • Boost@lemmy.world
          link
          fedilink
          English
          arrow-up
          1
          ·
          3 days ago

          I am in software and I don’t think it’s that clear cut tbh. There’s definitely a right and wrong way to use AI. I think a lot of companies are moving fast and breaking things right now, but a lot of them are going to find out that the thing they broke is the product and they won’t be able to slop their way out of a problem they slopped their way into.

          At a micro scale, AI is pretty good at writing workable code quickly. This obviously boosts productivity at the individual level, especially in the short term. At a macro scale, good maintainable software requires higher order thinking that transformer based models simply cannot do. So a lot of the stochastic micro decisions an AI makes lead to technical debt that is not trivial to remove, and can’t really be resolved by the AI itself, at least not in a way that won’t contribute to the problem.

          These issues can be curbed by the programer at the point of origin, before it gets out of hand, but obviously that requires more judicious use which cuts into the productivity gains. Because writing code has never been the hard part of software.

          TL;DR: fully embracing the slop machine will eventually poison your product in a way that is not really easily recoverable. It is useful, but not “too good to not use.”

      • Fallibilist@feddit.uk
        link
        fedilink
        English
        arrow-up
        3
        arrow-down
        10
        ·
        3 days ago

        What good could hundred thousand of the world’s best scientists do for me if they had decades to study every question I asked and could answer them immediately?

        Nothing I guess if you absolutely want to figure it all out by yourself.

      • mholiv@lemmy.world
        link
        fedilink
        English
        arrow-up
        3
        arrow-down
        8
        ·
        3 days ago

        AGI “use” has ethical issues of its own in its own right. But if we dismiss those (we shouldn’t) they will be extremely useful.

        Imagine a personal assistant that will organize your life and manage all the trivial but tedious tasks in your life. There is a reason why crazy rich people all hire personal assistants.

        • NonconfrontationaI@lemmy.ml
          link
          fedilink
          English
          arrow-up
          8
          arrow-down
          1
          ·
          3 days ago

          It’s because they’re lazy, stupid, and have more money than they know what to do with. I don’t have any of those luxuries.