They’ll slow down not because they “are worried” but because their improvements are stagnating as they hit financial and technical challenges.
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).
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.
There's probably something in how you design the models or chips or some other thing that will be figured out over the next 5 - 10 years to make these use dramatically less electricity.
But the growth in the scope and usage of AI is poised to grow exponentially, assuming this isn't a bubble.
After all GPUs were not really designed with AI efficiency in mind, and current AI architecture was not really designed with efficiency in mind, so there's probably some things that can be done. Over 5-10 years, who knows how much more efficient things could get?
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?
So if the new models they can develop right now are less frontier, it could be a net loss on their balance sheets.
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.
If you still think there's a stall despite all evidence pointing to opposite, I don't know what to say..
Edit:
The "reputable academic" who accused OpenAI had to say this about LLMs and the recent result.
source: https://cims.nyu.edu/~tristanb/statement.pdf
> “the results are not the important thing.”
> “the important thing is instead the significance that a mathematician and an LLM model can now do all this work in a month.”
> “This is a Deep Blue-Kasparov moment.”
> “incredibly important developments.”
> “If indeed an OpenAI model did close the gap to Navier-Stokes, that is a remarkable thing and it should be said loudly, by them, with the history intact.”
Clearly Buckmaster (who is probably one of the most accomplished academics in the field) himself doesn't believe that AI has stalled. What makes you think you are right?
I will note the remarkable goal post shift in your edit - giving direct counter evidence to your own earlier claim of an OpenAI proof - and leave it at that.
Unfortunately, there will be people that refuse to tackle the issue head on and will instead narrow their focus on data that suggests that tomorrow will be like today.
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.
Say what? Could lead to extinction, sure. Does? And nobody honestly argues otherwise? Baloney.
I guess people are just going to keep spreading misinformation about this, along the same lines as "Anthropic's C compiler fails on hello world". There is zero indication that they stole anything, unless it counts as "stealing" to spin up a bunch of compute based on rumors that the problem had been solved already.
Their best models might be quite good when directed at extremely difficult and very focused problems, but most business use cases are nothing like that.
Edit:
Not trying to imply these new frontier models aren’t also better at other things, just that there’s really no reason for most people to use them when cheaper alternatives exist that get the job done just as well.
Are these real step changes - big picture wise, or refinements in RL/agentic orchestration/"taste" and advancements due to bigger models and hardware technology/capacity scaling? If they not, does this tactic - and hardware improvements - continue to scale non-linearly like they need to?
It is clear that whatever does change in each model increment has resulted in meaningfully better end user capabilities (as well as regressions in some areas, honestly), but that doesn't prove anything. I'm not sure what I personally believe, but stating with your full chest that a stall is ridiculous ignores a lot of potential evidence to the contrary.
Stupid example: Astra. Its main improvements are: much much better computer use and 3d modeling capabilities; better subagent orchestration; better and more reliable tool use; slightly worse coding.
This looks to me, from a feature perspective, to be an incremental improvement across several functional areas, plus new features which are unquestionably excellent but are probably the result of RL focus, not magic.
Step change? Ehhhh depends on how you squint. But how many more iterations of this do we have? Are we going to squeeze quintillion parameter transformers into GPUs?
This is a ploy for regulatory capture.
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.
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
The other part is that this is 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.
I used 76 million sol tokens on Saturday, I have 45% still left on the week and I still have two full resets to use before October. For $20.
I used $61 dollars in Fable 5.1 credits too this weekend because I have to use that up this week. I paid nothing for those besides my $20 a month subscription.
How much would I pay at the actual API price? Nothing. Zero. My demand would drop to zero because I would just use the cheaper alternatives.
If a doughnut shop is giving away free doughnuts 24/7 my demand for doughnuts is going to go way up too. Through the roof actually because I know a doughnut shop can't give away doughnuts forever. Giving away free fancy doughnuts is not a sustainable business model.
I mean, my uneducated guess is that it's probably within the laws of physics for us to have at least 100x as much compute in the world as there is now. There would be a lot of engineering challenges, but I think it's physically possible. If so, OAI could double for at least a few more years.
I've seen more local opposition to datacentres than anything else, and the fact we have discretionary planning (which can't be abolished for political reasons, despite it amounting to putting economic sanctions on ourselves) means there's a lot of stakeholder vetos in the system.
It probably does make sense to build them close to the natural gas wells or other sources of power anyways.
Well, as a starter, I've been told that AI will take my job for at least 3 years now. That's not happening. In fact, what's happening is that I now have an AI vendor BEGGING me to use their product, which of course, cannot do my job.