5 ms·

They’ll slow down not because they “are worried” but because their improvements are stagnating as they hit financial and technical challenges.

kypro 3d ago
> because their improvements are stagnating as they hit financial and technical challenges. I don't mean to be rude, but how is it even possible for someone to hold this opinion in mid-2026? Can you explain why you believe this?
- dumberquestions 3d ago
  I don't think the technical aspect is true, performance has been growing fairly consistently, but the financial aspect, or more accurately the logistical aspect, is plausible; with competition as fierce as it currently is, for how long can they keep growing at the same pace? People can't afford RAM anymore and datacenter build outs aren't particularly popular, OAI has been doubling compute capacity every 7 months for the past 3 years, it's just physically impossible for this to go on for long, something has to give. And this is not to say that the tech isn't revolutionary or the demand isn't there, it's simply just currently too competitive, and to avoid getting into anti trust trouble they need to involve the government. Note this being a plausible doesn't necessarily make it true, for all I know they could have witnessed some safety incident and decided they need a pause, or maybe it's both reasons.
  - simianwords 3d ago
    I just find it strange how multiple people throw completely different arguments just to land on same conclusion. Your argument seems to mix a few arguments like: OpenAI has so much demand and it has made so much compute that it is a bad thing (?!). It can't go on (why?) hence the capabilities are stalling (how?). Then you also say that it is too competitive which is a totally different argument to compute. So in this thread we have multiple vectors of arguments like - high competition - high demand for compute (not sure how this hurts OpenAI but whatever) - capability has stalled
    - dumberquestions 3d ago
      I never mentioned capability stalling, my point is that if you extrapolate the same rate of growth just a few years into the future, you quickly reach logistical impracticality, I don't think It's hard to deduce that AI compute can't keep doubling every 6 months for long. The other part is that this happening because the foundational model business is both extremely successful and competitive, if it wasn't as successful the market demand would've been saturated by now, and if it wasn't as competitive a single monopoly could've paced things more reasonably from the beginning.
- simianwords 3d ago
  huge problem in discourse is that there are real interesting wedges in debate like p(doom) and RSI. but zitronion thought is not the real interesting wedge and almost everyone is on this side. - AI can't be profitable (lol) - everything is hype - HF incident was a conspiracy between HF, METR, OpenAI, Anthropic to drive up market share - Navier Stokes was solved because they literally looked at one of the codex chats and presented as their own (lol)
  - ofjcihen 3d ago
    I mean, more simply (and with less vitriol) - AI has yet to be profitable for these large labs (also zero moat etc.) - There is considerable hype and people are tired of it. - HF incident (and apparently many others that these labs are not reporting on or don’t even know about) proves they have terrible security practices and that’s about it. - NS is incredibly suspicious timing wise. You are sprinting around these threads to misrepresent the average persons issues with AI. I don’t know why people having those issues seems to be taken as a personal attack for you.
- johnnienaked 3d ago
  How can you not believe it? Neither of them are even close to making a profit and the market is saturated with cheaper alternatives. This is a ploy for regulatory capture.
  - Footnote7341 3d ago
    You're wrong about profits.
    - quikoa 3d ago
      Are you sure you don't mean revenue? Given the enormous investments profits seem very unlikely.
- tuvix 3d ago
  Why would someone hold the opposite opinion? It’s much more likely that our current approach to large language models for general use will eventually show diminishing improvements (even if you think it hasn’t yet), than the opposite situation where valuable improvements can be made forever. The threat of distillation and efficiency gains from competitors mean that providing value at the top end of the market is an existential necessity for these labs. I don’t think they can do that forever and, in my opinion, for the vast majority of use cases we’ve already reached very little improvement for new models when compared with available offerings.
  - simianwords 3d ago
    Sorry, this is ridiculous. OpenAI said that they have a step change in model performance. They proved it by solving a Millenium problem. HF incidents are public and vetted. If you still think there's a stall despite all evidence pointing to opposite, I don't know what to say..
    - vrganj 3d ago
      What reason could OpenAI possibly have to lie about their own performance? The fact they were desperate enough for a PR win they stole the research leading to the Millenium problem further hurts their case imo.
      - snaking0776 3d ago
        Two things can be true. Open AI is a huge company. 1. It has people in it who are career obsessed and who are willing to ruthlessly go after any opportunity to improve their standing/stock valuation. Using a 2 week old model to snipe a millenium prize for PR is in line with that. 2. There are many researchers and even executives at the company who genuinely think we are speedrunning the end of the world. I don’t know anyone in this field who honestly argues that if we build ASI soon it doesn’t lead to extinction. This group of people can output warnings about the state of research and fears for the future while pushing for regulation out of genuine fear of what they’re building. I tend to agree with them. You can’t view these companies as a monolith. They’re actions won’t be consistent because it’s built of many people with conflicting beliefs. Please look at arguments regarding AI risk and the current pace of progress and value them as it relates to the argument itself, not who said it. We are in a dangerous place and no one is sure how quickly we’ll get to a bad spot.
- Zenul_Abidin 3d ago
  Basically, continuously building out compute is costing these labs enormous amounts of money, which VCs and other companies have been bankrolling in order for them to develop powerful models. So if the new models they can develop right now are less frontier, it could be a net loss on their balance sheets.
asdfman123 3d ago
Actually, one of the major challenges they'll face is getting enough electricity. That could stop AI growth in its tracks.
- darth_avocado 3d ago
  I think it’s more than money and slowing progress. Public perception on AI is in the gutter. That is a much bigger threat to these companies. They’re trying to turn it around.
  - batshit_beaver 3d ago
    Trying to turn it around by once again claiming that ai is an existential threat and will take everyone’s job right before brutally murdering every human. These companies don’t appear to give a single fuck about public perception. Only their investors and the government (in anticipation of the biggest bailout in human history).
  - asdfman123 3d ago
    Public perception is another big one. But I think with the way AI is slated to grow exponentially it's going to hit electricity limits very soon. Big tech can build a huge data center in 5 years but scaling up the electrical infrastructure is mired in red tape and can take on the order of decades.
    - anjel 3d ago
      How did modernization get subsumed into scaling up. The us power grid has been outdated tech for decades
- dham 3d ago
  And the reason they get enough electricity is because people did the same scare tactics in the 70's against nuclear.

kypro 3d ago

> because their improvements are stagnating as they hit financial and technical challenges. I don't mean to be rude, but how is it even possible for someone to hold this opinion in mid-2026? Can you explain why you believe this?

dumberquestions 3d ago
I don't think the technical aspect is true, performance has been growing fairly consistently, but the financial aspect, or more accurately the logistical aspect, is plausible; with competition as fierce as it currently is, for how long can they keep growing at the same pace? People can't afford RAM anymore and datacenter build outs aren't particularly popular, OAI has been doubling compute capacity every 7 months for the past 3 years, it's just physically impossible for this to go on for long, something has to give. And this is not to say that the tech isn't revolutionary or the demand isn't there, it's simply just currently too competitive, and to avoid getting into anti trust trouble they need to involve the government. Note this being a plausible doesn't necessarily make it true, for all I know they could have witnessed some safety incident and decided they need a pause, or maybe it's both reasons.
- simianwords 3d ago
  I just find it strange how multiple people throw completely different arguments just to land on same conclusion. Your argument seems to mix a few arguments like: OpenAI has so much demand and it has made so much compute that it is a bad thing (?!). It can't go on (why?) hence the capabilities are stalling (how?). Then you also say that it is too competitive which is a totally different argument to compute. So in this thread we have multiple vectors of arguments like - high competition - high demand for compute (not sure how this hurts OpenAI but whatever) - capability has stalled
  - dumberquestions 3d ago
    I never mentioned capability stalling, my point is that if you extrapolate the same rate of growth just a few years into the future, you quickly reach logistical impracticality, I don't think It's hard to deduce that AI compute can't keep doubling every 6 months for long. The other part is that this happening because the foundational model business is both extremely successful and competitive, if it wasn't as successful the market demand would've been saturated by now, and if it wasn't as competitive a single monopoly could've paced things more reasonably from the beginning.
simianwords 3d ago
huge problem in discourse is that there are real interesting wedges in debate like p(doom) and RSI. but zitronion thought is not the real interesting wedge and almost everyone is on this side. - AI can't be profitable (lol) - everything is hype - HF incident was a conspiracy between HF, METR, OpenAI, Anthropic to drive up market share - Navier Stokes was solved because they literally looked at one of the codex chats and presented as their own (lol)
- ofjcihen 3d ago
  I mean, more simply (and with less vitriol) - AI has yet to be profitable for these large labs (also zero moat etc.) - There is considerable hype and people are tired of it. - HF incident (and apparently many others that these labs are not reporting on or don’t even know about) proves they have terrible security practices and that’s about it. - NS is incredibly suspicious timing wise. You are sprinting around these threads to misrepresent the average persons issues with AI. I don’t know why people having those issues seems to be taken as a personal attack for you.
johnnienaked 3d ago
How can you not believe it? Neither of them are even close to making a profit and the market is saturated with cheaper alternatives. This is a ploy for regulatory capture.
- Footnote7341 3d ago
  You're wrong about profits.
  - quikoa 3d ago
    Are you sure you don't mean revenue? Given the enormous investments profits seem very unlikely.
tuvix 3d ago
Why would someone hold the opposite opinion? It’s much more likely that our current approach to large language models for general use will eventually show diminishing improvements (even if you think it hasn’t yet), than the opposite situation where valuable improvements can be made forever. The threat of distillation and efficiency gains from competitors mean that providing value at the top end of the market is an existential necessity for these labs. I don’t think they can do that forever and, in my opinion, for the vast majority of use cases we’ve already reached very little improvement for new models when compared with available offerings.
- simianwords 3d ago
  Sorry, this is ridiculous. OpenAI said that they have a step change in model performance. They proved it by solving a Millenium problem. HF incidents are public and vetted. If you still think there's a stall despite all evidence pointing to opposite, I don't know what to say..
  - vrganj 3d ago
    What reason could OpenAI possibly have to lie about their own performance? The fact they were desperate enough for a PR win they stole the research leading to the Millenium problem further hurts their case imo.
    - snaking0776 3d ago
      Two things can be true. Open AI is a huge company. 1. It has people in it who are career obsessed and who are willing to ruthlessly go after any opportunity to improve their standing/stock valuation. Using a 2 week old model to snipe a millenium prize for PR is in line with that. 2. There are many researchers and even executives at the company who genuinely think we are speedrunning the end of the world. I don’t know anyone in this field who honestly argues that if we build ASI soon it doesn’t lead to extinction. This group of people can output warnings about the state of research and fears for the future while pushing for regulation out of genuine fear of what they’re building. I tend to agree with them. You can’t view these companies as a monolith. They’re actions won’t be consistent because it’s built of many people with conflicting beliefs. Please look at arguments regarding AI risk and the current pace of progress and value them as it relates to the argument itself, not who said it. We are in a dangerous place and no one is sure how quickly we’ll get to a bad spot.
Zenul_Abidin 3d ago
Basically, continuously building out compute is costing these labs enormous amounts of money, which VCs and other companies have been bankrolling in order for them to develop powerful models. So if the new models they can develop right now are less frontier, it could be a net loss on their balance sheets.

asdfman123 3d ago

Actually, one of the major challenges they'll face is getting enough electricity. That could stop AI growth in its tracks.

darth_avocado 3d ago
I think it’s more than money and slowing progress. Public perception on AI is in the gutter. That is a much bigger threat to these companies. They’re trying to turn it around.
- batshit_beaver 3d ago
  Trying to turn it around by once again claiming that ai is an existential threat and will take everyone’s job right before brutally murdering every human. These companies don’t appear to give a single fuck about public perception. Only their investors and the government (in anticipation of the biggest bailout in human history).
- asdfman123 3d ago
  Public perception is another big one. But I think with the way AI is slated to grow exponentially it's going to hit electricity limits very soon. Big tech can build a huge data center in 5 years but scaling up the electrical infrastructure is mired in red tape and can take on the order of decades.
  - anjel 3d ago
    How did modernization get subsumed into scaling up. The us power grid has been outdated tech for decades
dham 3d ago
And the reason they get enough electricity is because people did the same scare tactics in the 70's against nuclear.