Are we reading the same website? The predictions for China are completely fantastical - they are not falling behind and if anything the gap is narrowing, and they aren't stealing the weights because they don't need to (distilling is enough). Also the CDZ stuff is just fanfiction at this point.
Distillation only lets you keep pace with released models. By all indication, OpenAI/Anthropic’s unreleased internal models are so far ahead of Astra/Fable and every other lab that the chance of anyone else catching up is rapidly closing.
That's more a function of the amount of compute they can throw at it. They can afford to let an agent run in a loop for longer than you and I can. Its not proof of a vastly superior model.
Not proof but it does waggle it's eyebrows suggestively!
Like sure the marketing is undoubtedly overblown. But in 2025 there was no amount of money you could spend to make such impressive but weirdly unreadable progress.
Agreed but the math results don't seem out of reach for the publicly available models in 2026. Certainly, they have an unrefined but superior internal model. But the math results don't prove said internal model would be as big of a leap if released today as Mythos was when it was announced.
We don't have any information other than that they are capable enough of solving unsolved math problems. Are they good at writing a good movie script? Do they understand protein ligand interactions? Who knows. Let's wait till they release the model
Do you have any source for any of that? Also haven't people been saying that China would be hopelessly distanced for the better part of 2 years, only to be proven wrong over and over again? Deepseek-r1, kimi k3, etc.
People said the same about mythos, and o3, and gpt-4.
Most of the very recent spectacular achievements (math conjectures) were done by leveraging datacenter capacity (throwing agents and millions' worth of compute at the wall until something sticks), not any secret sauce intelligence.
No matter what happens, people just blindly claim this nonsense is still accurate. We could have AI halt tomorrow and people on Hacker News would still claim AI 2027 is on track.
Everything starting from mid-2026 is incredibly wrong, which is pretty poor predictive performance considering they published it mid-2025. List of misses:
- In mid-2026, China will be six months behind the released models of the American labs. (In mid-2026, China released Kimi K3, which was equivalent to the best released U.S. model at the time, Claude Fable.)
- In mid-2026, China will nationalize all domestic AI labs and centralize them into a new special economic zone, the "CDZ," created around a nuclear reactor. 80% of all chips in China will be redirected to the CDZ. This uh. Obviously didn't happen.
- In late 2026 OpenAI/Anthropic will release a tiny model that outperforms their previously-best 2026 model (Astra/Fable), that is priced 10x cheaper, and they will market fine-tuning for it. (Lol.)
- AI will increase the stock market by late 2026 by 30% (in fact the S&P 500 is up 13.9% YTD, which is pretty good, but not at all out of the ordinary).
Their predictions for 2027 also seem pretty wrong: e.g. they expect continual learning to be solved in January, and RSI including from a research perspective, not just "optimize CUDA kernels," to also be solved in January, which I suspect no serious lab employee believes anymore. Most lab employees believe RSI will happen (as do I!), of course, but not in two and a half months.
By early 2027 they expect cyberwar with China because China has stolen the weights of a model and smuggled it into the CDZ.
By mid-2027 they expect true superintelligence, where essentially all engineers and researchers are useless, unable to comprehend the advances the AI is able to make and largely unable to even usefully manage or steer AI, who are better at self-managing than a human would be.
Considering their 2025-mid-2026 predictions were basically "progress continues as normal and nothing crazy happens," it's not super surprising that they were more or less right about that. Their 2026/2027 predictions were the spicy ones, and none of them have happened, or are even on track to happening!
The Chinese model lag depends on who you ask, but the current estimate seems to be about four months: https://stateofopensource.ai/
> In late 2026 OpenAI/Anthropic will release a tiny model that outperforms their previously-best 2026 model (Astra/Fable), that is priced 10x cheaper
We don't know the sizes of any of these, but GPT Luna and Claude Haiku 5.5 are tremendously competitive for their cost, and in some ways beat their larger-sized predecessors. I'd say there's enough doubt that I'd be willing to provide partial points to this claim. (No finetuning, yes.)
The prediction was a 10x price reduction, so equivocating about "we don't know the size" doesn't save their prediction — a 10x price reduction would imply the model was likely more than 10x smaller in parameter count, and the price factored heavily in their prediction (they predicted its low cost would destroy other competition, since no one else could have such a capable model at that low price). And Haiku/Luna are nowhere near competitive with Astra or Fable, which doubly damns their prediction. I'm surprised you would pooh pooh the equivalence of K3 and original-Fable (which has been widely shown across many different benchmarks and even human preference data), while claiming an equivalence between Haiku and Fable!
If you stretch the definition of "previously-best 2026 model" a bit, Haiku 5.5 outperforms Opus 4.6 which was their best at some point in 2026 while being 10x cheaper.
What special sauce exactly? Refusing to work on any problems remotely connected to biology (including e.g. the book of Genesis)?
>The Chinese model lag depends on who you ask, but the current estimate seems to be about four months: https://stateofopensource.ai/
Benchmaxxing aside, most actual performance is now harness and orchestration dependent and the difference between frontier US and Chinese models is dim as best for virtually all practical tasks. The vast majority of people don't need to solve Navier-Stokes
>In late 2026 OpenAI/Anthropic will release a tiny model that outperforms their previously-best 2026 model (Astra/Fable), that is priced 10x cheaper, and they will market fine-tuning for it. (Lol.)
Opus 5.5 might not be 10x cheaper but it finally made me not hit the limits constantly.
Yeah I think we are slightly ahead of the prediction on coding capabilities right now. AI 2027 predicts Superhuman Coder in March 2027 but I think my expectation for it is 1-2 months earlier right now
If one believes Zitron / Microsoft claims that like ~50% of AI chips bought are in warehouses, and current projected DC delays... the TLDR is the amount of compute lead (aka what drives lead) is fraction of projection, which will shift timelines accordingly. And really if DC build out delays is due to infra or scrubbed altogether, we're talking about years.
Did you read it to the end? It is insane speculative fiction. They are not even qualitatively right about one of the main narrative planks, which is that by now (mid-late 2026) there would be one clearly dominant company each in the U.S. and China, and that the latter would be nationalizing their compute.
Are we reading the same website? The predictions for China are completely fantastical - they are not falling behind and if anything the gap is narrowing, and they aren't stealing the weights because they don't need to (distilling is enough). Also the CDZ stuff is just fanfiction at this point.
Distillation only lets you keep pace with released models. By all indication, OpenAI/Anthropic’s unreleased internal models are so far ahead of Astra/Fable and every other lab that the chance of anyone else catching up is rapidly closing.
I suspect this is more marketing than fact. I don't think there's any real evidence that this is the case, just hints dropped by OpenAI and Anthropic.
Well, except the giant dump of math problems they just solved with an internal model.
That's more a function of the amount of compute they can throw at it. They can afford to let an agent run in a loop for longer than you and I can. Its not proof of a vastly superior model.
Not proof but it does waggle it's eyebrows suggestively!
Like sure the marketing is undoubtedly overblown. But in 2025 there was no amount of money you could spend to make such impressive but weirdly unreadable progress.
Agreed but the math results don't seem out of reach for the publicly available models in 2026. Certainly, they have an unrefined but superior internal model. But the math results don't prove said internal model would be as big of a leap if released today as Mythos was when it was announced.
We don't have any information other than that they are capable enough of solving unsolved math problems. Are they good at writing a good movie script? Do they understand protein ligand interactions? Who knows. Let's wait till they release the model
Do you have any source for any of that? Also haven't people been saying that China would be hopelessly distanced for the better part of 2 years, only to be proven wrong over and over again? Deepseek-r1, kimi k3, etc.
I've seen the same sentiments/reports, from X accounts known to talk to leakers.
People said the same about mythos, and o3, and gpt-4.
Most of the very recent spectacular achievements (math conjectures) were done by leveraging datacenter capacity (throwing agents and millions' worth of compute at the wall until something sticks), not any secret sauce intelligence.
That's not true, actually.
The last round they said they averaged one prompt, one agent, and 3 hours' work.
it is quite widely known that the chinese models are just quite shit for math. i think for coding tasks they really do quite alright.
No matter what happens, people just blindly claim this nonsense is still accurate. We could have AI halt tomorrow and people on Hacker News would still claim AI 2027 is on track.
Five years past the flare
a bottle drifts with its note
AI singularity next year
i thought it was meant as more of a thought experiment than a prediction?
Everything starting from mid-2026 is incredibly wrong, which is pretty poor predictive performance considering they published it mid-2025. List of misses:
- In mid-2026, China will be six months behind the released models of the American labs. (In mid-2026, China released Kimi K3, which was equivalent to the best released U.S. model at the time, Claude Fable.)
- In mid-2026, China will nationalize all domestic AI labs and centralize them into a new special economic zone, the "CDZ," created around a nuclear reactor. 80% of all chips in China will be redirected to the CDZ. This uh. Obviously didn't happen.
- In late 2026 OpenAI/Anthropic will release a tiny model that outperforms their previously-best 2026 model (Astra/Fable), that is priced 10x cheaper, and they will market fine-tuning for it. (Lol.)
- AI will increase the stock market by late 2026 by 30% (in fact the S&P 500 is up 13.9% YTD, which is pretty good, but not at all out of the ordinary).
Their predictions for 2027 also seem pretty wrong: e.g. they expect continual learning to be solved in January, and RSI including from a research perspective, not just "optimize CUDA kernels," to also be solved in January, which I suspect no serious lab employee believes anymore. Most lab employees believe RSI will happen (as do I!), of course, but not in two and a half months.
By early 2027 they expect cyberwar with China because China has stolen the weights of a model and smuggled it into the CDZ.
By mid-2027 they expect true superintelligence, where essentially all engineers and researchers are useless, unable to comprehend the advances the AI is able to make and largely unable to even usefully manage or steer AI, who are better at self-managing than a human would be.
Considering their 2025-mid-2026 predictions were basically "progress continues as normal and nothing crazy happens," it's not super surprising that they were more or less right about that. Their 2026/2027 predictions were the spicy ones, and none of them have happened, or are even on track to happening!
Agree with most of this, but:
> In mid-2026, China released Kimi K3, which was equivalent to the best released U.S. model at the time, Claude Fable.
I don't think this was, or is, true: https://artificialanalysis.ai/evaluations/artificial-analysi... - even from a vibe check alone, it was pretty clear that K3 was missing Fable's special sauce, especially for more hands-on problems.
The Chinese model lag depends on who you ask, but the current estimate seems to be about four months: https://stateofopensource.ai/
> In late 2026 OpenAI/Anthropic will release a tiny model that outperforms their previously-best 2026 model (Astra/Fable), that is priced 10x cheaper
We don't know the sizes of any of these, but GPT Luna and Claude Haiku 5.5 are tremendously competitive for their cost, and in some ways beat their larger-sized predecessors. I'd say there's enough doubt that I'd be willing to provide partial points to this claim. (No finetuning, yes.)
The prediction was a 10x price reduction, so equivocating about "we don't know the size" doesn't save their prediction — a 10x price reduction would imply the model was likely more than 10x smaller in parameter count, and the price factored heavily in their prediction (they predicted its low cost would destroy other competition, since no one else could have such a capable model at that low price). And Haiku/Luna are nowhere near competitive with Astra or Fable, which doubly damns their prediction. I'm surprised you would pooh pooh the equivalence of K3 and original-Fable (which has been widely shown across many different benchmarks and even human preference data), while claiming an equivalence between Haiku and Fable!
If you stretch the definition of "previously-best 2026 model" a bit, Haiku 5.5 outperforms Opus 4.6 which was their best at some point in 2026 while being 10x cheaper.
>I don't think this was, or is, true: https://artificialanalysis.ai/evaluations/artificial-analysi... - even from a vibe check alone, it was pretty clear that K3 was missing Fable's special sauce, especially for more hands-on problems
What special sauce exactly? Refusing to work on any problems remotely connected to biology (including e.g. the book of Genesis)?
>The Chinese model lag depends on who you ask, but the current estimate seems to be about four months: https://stateofopensource.ai/
Benchmaxxing aside, most actual performance is now harness and orchestration dependent and the difference between frontier US and Chinese models is dim as best for virtually all practical tasks. The vast majority of people don't need to solve Navier-Stokes
>In late 2026 OpenAI/Anthropic will release a tiny model that outperforms their previously-best 2026 model (Astra/Fable), that is priced 10x cheaper, and they will market fine-tuning for it. (Lol.)
Opus 5.5 might not be 10x cheaper but it finally made me not hit the limits constantly.
Wow shocker. Crazy unfounded prediction website that lots of people said was bupkis at the time turned out to be wrong
Probably a bit ahead of it.
Yeah I think we are slightly ahead of the prediction on coding capabilities right now. AI 2027 predicts Superhuman Coder in March 2027 but I think my expectation for it is 1-2 months earlier right now
I’m still putting it at 2029 for real-world work acceleration.
If one believes Zitron / Microsoft claims that like ~50% of AI chips bought are in warehouses, and current projected DC delays... the TLDR is the amount of compute lead (aka what drives lead) is fraction of projection, which will shift timelines accordingly. And really if DC build out delays is due to infra or scrubbed altogether, we're talking about years.
Pretty amazingly accurate
Did you read it to the end? It is insane speculative fiction. They are not even qualitatively right about one of the main narrative planks, which is that by now (mid-late 2026) there would be one clearly dominant company each in the U.S. and China, and that the latter would be nationalizing their compute.
Damn this is terrifying, I kinda wish I hadn't read this
Yep we're basically inventing all of the RSI loops that AI 2027 thought we'd invent lol.