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 🖇️)
It’s not that it won’t improve, but it isn’t going to cause a runaway “singularity” event.
Like the drama around the models “escaping” and “amazing hacks” have turned out to be something, but not nearly what people were afraid it was going to be.
A lot of the fundamental limitations have remained, and we are figuring out the scenarios where those limitations are fine or there is a way to create a feedback mechanism to try to reroll the AI until it passes. Lots of success there, but the fundamental disconnects are still there, just not important for the task at hand or can be worked around.
That might very well be, and would probably be the best outcome we can hope for. I guess we’ll see the shape of the curve in the next year-ish - if recursive self-improvement hasn’t come into play for real by then, I can’t see how the current investment level is defensible (but I’m not sure I see that now, so who knows)
The way people reach that extremely logical conclusion is by looking at 1) the diminishing returns of continued training and of building new models, 2) The data center buildout required for those diminishing returns is rising exponentially in cost, leading to many planned centers being cancelled and/or running behind schedule, 3) These LLMs are not even close to profitable, and they are not useful enough to justify the cost of using them.
As they continue to attempt to improve the LLMs, the costs rise exponentially, the results (and profitability) do not.
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.
Yeah, I’m fairly confident that they’re near the ceiling of what is possible with the current technology.
Also there’s so much slop out there now that LLMs are beginning to train on the slop and effectively giving themselves a sort of digital folding prion disease.
I follow a lot of journalists who cover AI specifically, and everything I’m seeing shows quality increasing more slowly over time as the cost builds at an increasing rate.
The financial fuckery does make it hard to keep track of, but the fact that they’re even engaged in that sort of financing betrays that they are not in good financial health.
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).
In this scenario, why would companies start attempting to make big expensive chatbots again after they caused the worst financial fallout of all time? That would be likely the least advisable business move ever.
Similar to you, I would concede that my information sphere is influenced by my contempt for the technology (as well as by my love for computers in general)… thank you for being open to have a real conversation with me about this by the way. Most of the time I just end up getting attacked because pro-AI people don’t like what I have to say.
I would note tho, that there’s only a profit motive involved in one of these competing narratives, and that would be the narrative being pushed by the oligarchic techbro fascists.
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.
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:
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 🖇️)
It’s not that it won’t improve, but it isn’t going to cause a runaway “singularity” event.
Like the drama around the models “escaping” and “amazing hacks” have turned out to be something, but not nearly what people were afraid it was going to be.
A lot of the fundamental limitations have remained, and we are figuring out the scenarios where those limitations are fine or there is a way to create a feedback mechanism to try to reroll the AI until it passes. Lots of success there, but the fundamental disconnects are still there, just not important for the task at hand or can be worked around.
That might very well be, and would probably be the best outcome we can hope for. I guess we’ll see the shape of the curve in the next year-ish - if recursive self-improvement hasn’t come into play for real by then, I can’t see how the current investment level is defensible (but I’m not sure I see that now, so who knows)
The way people reach that extremely logical conclusion is by looking at 1) the diminishing returns of continued training and of building new models, 2) The data center buildout required for those diminishing returns is rising exponentially in cost, leading to many planned centers being cancelled and/or running behind schedule, 3) These LLMs are not even close to profitable, and they are not useful enough to justify the cost of using them.
As they continue to attempt to improve the LLMs, the costs rise exponentially, the results (and profitability) do not.
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.
Yeah, I’m fairly confident that they’re near the ceiling of what is possible with the current technology.
Also there’s so much slop out there now that LLMs are beginning to train on the slop and effectively giving themselves a sort of digital folding prion disease.
I follow a lot of journalists who cover AI specifically, and everything I’m seeing shows quality increasing more slowly over time as the cost builds at an increasing rate.
The financial fuckery does make it hard to keep track of, but the fact that they’re even engaged in that sort of financing betrays that they are not in good financial health.
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).
In this scenario, why would companies start attempting to make big expensive chatbots again after they caused the worst financial fallout of all time? That would be likely the least advisable business move ever.
Similar to you, I would concede that my information sphere is influenced by my contempt for the technology (as well as by my love for computers in general)… thank you for being open to have a real conversation with me about this by the way. Most of the time I just end up getting attacked because pro-AI people don’t like what I have to say.
I would note tho, that there’s only a profit motive involved in one of these competing narratives, and that would be the narrative being pushed by the oligarchic techbro fascists.
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.