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Joined 2 years ago
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Cake day: February 8th, 2025

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  • Good points as well. I guess my own view is coloured by having access to models that I find actually useful in my work. If my experience was only grating Claude prose and soulless AI “art” I’m not sure the tech itself would appeal all that much.

    Probably that also blinds me a bit to what you argue, but I agree that the reasoning is sound from a point of view where all AI is useless. I’m just not sure that other areas won’t have the same OMG moment that coding had earlier this year.


  • A year ago, that was my experience coding with AI as well. Sometime this spring that changed, especially when using coding agents, and lately (as I’ve stated elsewhere) the quality is on average pretty good. And contrary to what you’re implying, I’m not that easy to impress…

    If there’s anything I hope you take from this exchange, it’s that the capabilities of AI shouldn’t be a part of your arguments against the current SV mania. The concentration of power, the disregard for communities and the environment, the stated goals of replacing human labour, all of that (and a lot more!) is enough, but it is what surrounds the technology itself. That technology is advancing, maybe feeding on itself, so an attack based on what it can do now can become outdated (and I’d argue that some of yours already are).




  • Agree, in that case the development would probably be more incremental, focusing on what can be improved without hundreds of thousands of GPUs available, and moving inference maybe to a local-first setting. There would be no promise of 1000x profits from that, so maybe we’d get a more managable pace.

    Thank you too. I have the same feeling, just the other way around - lemmy seems to have little patience for even slight positivity towards AI and LLMs in particular. Having an actual discussion is refreshing.

    Regarding the profit motive, I concur, at least for the US side. I’m less certain about China, but I’m not very knowledgable there, so maybe the same mechanisms are in effect.


  • I don’t think “computer follows instruction” is the right angle to look at this from. The instructions that the literal computer followed were a ton of matrix multiplication operations. The consequences of that arithmetic is easier to analyze as the emergent behaviour of the “gestalt” that produces the words that calls the tools etc. (This is also the reason that dismissing the entire field as “stochastic parrots” and “spicy autocomplete” misses the mark - if you want to predict the next word all the way through a counterexample to the Jacobian Conjecture, it’s hard to see how that can be done without a - for lack of a better word - mental model of the problem)

    If you do any coding at all, I encourage you to look at what the latest models output. The average quality of work from a frontier model is amazing. Yes, there are bugs, but with adversarial auto-review it’s absolutely on par with a journeyman human programmer. The problem is of course that if you don’t hire junior programmers and let them do that work, you’ll never get new experts, and that’s a clear worry.

    My point with the national security angle was that if you extrapolate just a little bit from current capabilities, you get to a point where an “AI gap” is a problem, regardless of the techbro claims. Keeping a close eye on that is firmly within the responsibility of a national government. Personally, I don’t see any good outcomes from an AI race like that, unless we actually hit a hard ceiling on further expansion. Fingers crossed.


  • I’m not at all confident that they’re hitting a ceiling yet, and I suspect one’s outlook on that depends on how the information bubble you’re in is shaped. I concede that mine is influenced by my interest in the underlying technology.

    I do believe that even if the bubble popped right now, and the current models are the best we’ll get for the next ten years, that would be enough to have dramatic consequences (aside from the econuclear fallout from the crash, that is).


  • I mean, that’s a matter of definition, isn’t it? If I ask a coding agent or whatever to implement something, and it circumvents the sandbox to do it, causing damage in the process, I’d be comfortable calling that “going rogue”. I have had that happen, without the damage part, luckily. I guess you can counter that I asked it to do the something, but then I don’t think we agree on the definitions.

    I also think that if you’re against AI, you’d be doing yourself a disservice by not keeping up with the actual capabilities of the thing you oppose. The latest models are surprisingly good at e.g. coding, so basing your arguments on them being useless is not the most efficient strategy.

    To also be clear, I don’t see any way AI disappears now, so I believe we’ll have to make the best of it (and in complete isolation, it is an utterly fascinating area of - to me - complete science fiction). Ideally development slowed down now so we could regroup and adapt, but I’m not too hopeful. The maximalist techbro endgame is so obviously a matter of national security for both China and the US, that there’s no way either of them will dare to wind it down, in case SV is actually right.



  • Are they diminishing, though? Current open-ish Chinese models are near-SOTA, and they’ve been trained on less powerful chips than currently available to the frontier labs. I suspect there’s a lot more to be squeezed out here. Data center rollout slowing down might lead to the same effect in the US, but will probably only serve to cement the main players in place as the competition is locked out. Inference in isolation is profitable now, I think? Hard to tell with the Möbius net of creative financials, of course.

    I hope you’re right. A slowing of the frontier development would make it possible for the world to catch up and readjust, and maybe buy hardware again, to run the current crop of models locally. That in itself would be disruptive enough for me.


  • The current data center craze is a bit easier to understand when you realize that the sentiment in this passage from https://situational-awareness.ai/ permeates Silicon Valley thinking these days:

    The barriers to even trillions of dollars of datacenter buildout in the US are entirely self-made. Well-intentioned but rigid climate commitments (not just by the government, but green datacenter commitments by Microsoft, Google, Amazon, and so on) stand in the way of the obvious, fast solution. At the very least, even if we won’t do natural gas, a broad deregulatory agenda would unlock the solar/batteries/SMR/geothermal megaprojects. Permitting, utility regulation, FERC regulation of transmission lines, and NEPA environmental review makes things that should take a few years take a decade or more. We don’t have that kind of time.

    We’re going to drive the AGI datacenters to the Middle East, under the thumb of brutal, capricious autocrats. I’d prefer clean energy too—but this is simply too important for US national security. We will need a new level of determination to make this happen. The power constraint can, must, and will be solved.

    Hard to feel too sorry for his $35B paper loss…


  • Yes, phones and consumer gadgets are becoming “hot water” (at least for the affluent West). From that, he seemingly concludes that technology itself has no room for growth and development? I don’t quite follow his reasoning, but I notice a, dare I say, load-bearing sentence:

    As it becomes more and more clear that these machines are nothing like conscious people, that they don’t do runaway self-improvement, and that they won’t foment the apocalypse, […]

    Questions of consciousness aside, I don’t see how you can look at the developments of the last few years and conclude that AI is over, and that self-improvement is tapering off. To me, that’s still very much an unknown, and the latest model releases makes me lean more exponential than sigmoidal.

    (I don’t particularly want to be right here, since I see the chances of us getting the Culture as rather slim 🖇️)