Funny how they include nvidia, micron, and AMD revenue as “AI revenue” and that it represents that majority of industry revenue but presumably a big chunk of everyone else’s spend. Almost might as well include electric utility revenue as AI Revenue by that metric
AI is more like an ongoing research project than it is a product. GPUs are currently the product that is profitable and Nvidia will keep funding labs to keep buying GPUs.
This is exactly how Cloud Computing looked in 2012-2018. Dumping huge $ into computing buildout that wasn't profitable yet. All those co's: Amazon, GCP, Azure paid off immensely and are ridiculously profitable.
No, it wasn't. Cloud computing was almost immediately profitable.
And Amazon was famously "unprofitable" for their first 9 years because they were investing all their very real profits into a form of capital that the US tax code didn't recognize.
IIRC Amazon chose to reinvest early revenue to grow AWS intentionally, and the revenue curve eventually evened out and obviously surpassed expenses. The problem with the AI buildout is that there's not a ton of evidence that these companies are approaching profitability, we can't even know because they're private.
Amazon's incubation of AWS was methodical and transparent. OpenAI is saying that they don't expect to be profitable until at least 2030, with over a trillion dollars in committed spend before that point. It's the largest "trust me bro" play in human history.
Yes, they said that about a lot of companies that dumped product until the competition was eliminated, then abused their monopoly position and resultant political connections to do whatever they wanted. Their sites are worse than ever. Literally worse than the day after launch.
My main issue with this timeline is that AI still has trouble transitioning to the real world. It predicts for 2029:
> There are swarms of insect-sized drones that can poison human infantry before they are even noticed; flocks of bird-sized drones to hunt the insects; new ICBM interceptors, and new, harder-to-intercept ICBMs. The rest of the world watches the buildup in horror, but it seems to have a momentum of its own.
Does anyone really predict insect drones _in production_ 3 years from now, to the degree that we need bird drones to hunt the insect drones? How the hell are these things powered?
Lean/math/millenienium prizes are "grindable" [0]. Wake me up when AI is making order-of-magnitude improvements in ungrindable real world tasks like batteries, hypersonic engine manufacturing, and stealth/silent motors that you can't hear.
I think the idea is that AI itself is going to massively accelerate its own development, and AI with real-world competence is coming very soon. At the rate things are going, it wouldn't suprise me at all if we had mass production of AI-designed systems in the next six months, actually.
> Does anyone really predict insect drones _in production_ 3 years from now
The industrial expansion timelinen as described in AI 2027 is way too compressed; I don't think any AI doomer believes that. The dynamics are plausible though, even without China stealing the weights.
Please elaborate: what dynamics? This is rather vague. My point is that AI can't grind real world physics/chemistry/engineering. What dynamics are in play here?
One of the most biased claims IMO in AI 2027 is that a huge portion of the geopolitical and existential risk argument is hinged on the notion that China just steals the US frontier weights.
Look what's coming out of China, they are catching up on performance and surpassing the US in efficiency. They're on a different level when it comes to open releases of weights.
I don't, to me the entire premise is a bit flawed at it's core (ASI), and I read it like bad science fiction with China playing the bad guy just a narrative crux so we get to the acceleration timeline and warring nation states.
>Agent-2, more so than previous models, is effectively “online learning,” in that it’s built to never really finish training. Every day, the weights get updated to the latest version, trained on more data generated by the previous version the previous day.
That seems to me to be a natural progression, from discrete models to models that are just continuously improved. Maybe we'll end up with different models with different rates of improvement rather than static differences in performance, and methodologies for that improvement will be the thing we care about. Maybe over time, even benchmark tests will be primarily concerned with that kind of efficiency.
I think a huge debate right now is the relative value of the "frontier" models from Western companies at the cutting edge, vs distilled versions of those models that are good enough and exponentially cheaper coming from China. But a paradigm of 'always training' means an always active, always advancing frontier, which is a stronger moat than a one-off model that's more advanced for a few months.
Interesting but it degenerates into sci-fi tropes if you look at the extrapolations. Reminds me of 90s writing about what the Internet was going to do.
The Internet ended up being both more incredible and more mundane than predicted.
Fun to read this again and see actual parallels. The 2030 Takeover section is such a ludicrous leap, however. None of the supply chain infrastructure, energy, or Moravec's Paradox realities are ever addressed. Turn the page and suddenly humanity is largely annihilated with a Corgi-esque human breed kept as pets. How did these robots emerge from utter rhetorical nothingness? Robocalypse impossible? Perhaps not. By 2030? an intellectually embarrassing farce worthy of a facepalm.
Sorry, but the notion that creative writing and robotaxi's exist as proof of anything is like saying my child can drive and write; and while true, the measure of that ability is not at the level of the best humans. It's average at best.
Depends what your definitions of "requires" and "full" are. On mine there's some nagging on the scale of once every tens to hundreds of seconds if it thinks I'm not paying attention. You're willingly living a more stressful and unsafe life if you're still manually driving your car in 2026.
I wonder when the people will get that intelligence is not only directed at the external, but only really starts when you look at the internal (joy, pleasure, traumas, taboos, awkwardness, abuse etc.). Look up the word "interoception".
https://isaiprofitable.com/
I like this one better
Funny how they include nvidia, micron, and AMD revenue as “AI revenue” and that it represents that majority of industry revenue but presumably a big chunk of everyone else’s spend. Almost might as well include electric utility revenue as AI Revenue by that metric
I don’t understand how they track these figures.
For example: META made a bit more than $5 bn revenue since 2022?
AI is more like an ongoing research project than it is a product. GPUs are currently the product that is profitable and Nvidia will keep funding labs to keep buying GPUs.
Oh look, the answer is the same when I looked a couple months ago. Interesting
Hey now, some of them reach -50% profit margins!
You almost have hope for them from the total number until you realize the vast majority of that green is made up of NVIDIA
This is exactly how Cloud Computing looked in 2012-2018. Dumping huge $ into computing buildout that wasn't profitable yet. All those co's: Amazon, GCP, Azure paid off immensely and are ridiculously profitable.
No, it wasn't. Cloud computing was almost immediately profitable.
And Amazon was famously "unprofitable" for their first 9 years because they were investing all their very real profits into a form of capital that the US tax code didn't recognize.
GCP reported its first quarterly operating profit in Q1 2023, roughly 15 years after Google began offering cloud computing.
Frontier labs are also reinvesting their tens of billions of revenue back into infra scaleout, sounds like Amazon.
If 2 of 3 were like this, and Azure numbers were never split out, want to take a guess what the economics of the third was like too?
the same type of people will eventually hate it when AI actually starts profiting at which point they will ask for redistribution.
damned if you do.
damned if you don't.
IIRC Amazon chose to reinvest early revenue to grow AWS intentionally, and the revenue curve eventually evened out and obviously surpassed expenses. The problem with the AI buildout is that there's not a ton of evidence that these companies are approaching profitability, we can't even know because they're private.
Amazon's incubation of AWS was methodical and transparent. OpenAI is saying that they don't expect to be profitable until at least 2030, with over a trillion dollars in committed spend before that point. It's the largest "trust me bro" play in human history.
On the other hand, people said this about Amazon, Google, Meta/Facebook, and loads of other huge tech things that are now wildly profitable.
It hasn't been a reliable predictive metric so far. All runaway growth tech sectors and businesses tend to look economically insane until they're not.
> and loads of other huge tech things that are now wildly profitable.
They also said it about loads of other huge tech things that died. Pointing at the ones that made it is literally survivor bias.
Yes, they said that about a lot of companies that dumped product until the competition was eliminated, then abused their monopoly position and resultant political connections to do whatever they wanted. Their sites are worse than ever. Literally worse than the day after launch.
My main issue with this timeline is that AI still has trouble transitioning to the real world. It predicts for 2029:
> There are swarms of insect-sized drones that can poison human infantry before they are even noticed; flocks of bird-sized drones to hunt the insects; new ICBM interceptors, and new, harder-to-intercept ICBMs. The rest of the world watches the buildup in horror, but it seems to have a momentum of its own.
Does anyone really predict insect drones _in production_ 3 years from now, to the degree that we need bird drones to hunt the insect drones? How the hell are these things powered?
Lean/math/millenienium prizes are "grindable" [0]. Wake me up when AI is making order-of-magnitude improvements in ungrindable real world tasks like batteries, hypersonic engine manufacturing, and stealth/silent motors that you can't hear.
[0]: https://www.dwarkesh.com/p/the-next-paradigm
I think the idea is that AI itself is going to massively accelerate its own development, and AI with real-world competence is coming very soon. At the rate things are going, it wouldn't suprise me at all if we had mass production of AI-designed systems in the next six months, actually.
> Does anyone really predict insect drones _in production_ 3 years from now
The industrial expansion timelinen as described in AI 2027 is way too compressed; I don't think any AI doomer believes that. The dynamics are plausible though, even without China stealing the weights.
Literally 2 days ago:
> The people building AI earnestly believe that it could kill us all by the end of the decade. This is not a marketing stunt.
https://x.com/hilbertspaess/status/2097476203863224394
> The dynamics are plausible
Please elaborate: what dynamics? This is rather vague. My point is that AI can't grind real world physics/chemistry/engineering. What dynamics are in play here?
I don't like grandiose claims about AI.
Mom said it was my turn to post this
One of the most biased claims IMO in AI 2027 is that a huge portion of the geopolitical and existential risk argument is hinged on the notion that China just steals the US frontier weights.
Biased how? China has a long history of corporate espionage.
Everyone knows the Chinese are capable of whatever they put their minds to. But stealing IP to skip some steps is part of the system.
Look what's coming out of China, they are catching up on performance and surpassing the US in efficiency. They're on a different level when it comes to open releases of weights.
I don't, to me the entire premise is a bit flawed at it's core (ASI), and I read it like bad science fiction with China playing the bad guy just a narrative crux so we get to the acceleration timeline and warring nation states.
good thing US is completely clean
Of course it's a spectrum that all advanced countries exist on, but if you think China and the US are on the same end of the spectrum, that's strange.
What country is supposed to be counterexample here, with zero history of corporate espionnage?
That's what a lot of American companies say.
Wait until you hear about Amazon's practices.
I'm probably going to be downvoted for this, but this makes this whole industry look like a bunch of snake oil salesmen and charlatans.
>Agent-2, more so than previous models, is effectively “online learning,” in that it’s built to never really finish training. Every day, the weights get updated to the latest version, trained on more data generated by the previous version the previous day.
That seems to me to be a natural progression, from discrete models to models that are just continuously improved. Maybe we'll end up with different models with different rates of improvement rather than static differences in performance, and methodologies for that improvement will be the thing we care about. Maybe over time, even benchmark tests will be primarily concerned with that kind of efficiency.
I think a huge debate right now is the relative value of the "frontier" models from Western companies at the cutting edge, vs distilled versions of those models that are good enough and exponentially cheaper coming from China. But a paradigm of 'always training' means an always active, always advancing frontier, which is a stronger moat than a one-off model that's more advanced for a few months.
So often people shy away from making predictions, which is a shame. I always love when people make the attempt and use their imagination.
I am an AI booster and have visibility into a number of these models, and this is ridiculous.
They underestimate AI's existing impact on some job markers and overestimate it's impact in such short a timeframe.
Interesting but it degenerates into sci-fi tropes if you look at the extrapolations. Reminds me of 90s writing about what the Internet was going to do.
The Internet ended up being both more incredible and more mundane than predicted.
Now that's some load-bearing seam if I ever seen one
Fun to read this again and see actual parallels. The 2030 Takeover section is such a ludicrous leap, however. None of the supply chain infrastructure, energy, or Moravec's Paradox realities are ever addressed. Turn the page and suddenly humanity is largely annihilated with a Corgi-esque human breed kept as pets. How did these robots emerge from utter rhetorical nothingness? Robocalypse impossible? Perhaps not. By 2030? an intellectually embarrassing farce worthy of a facepalm.
Dario likes this timeline. Good for the IPO valuation.
Sorry, but the notion that creative writing and robotaxi's exist as proof of anything is like saying my child can drive and write; and while true, the measure of that ability is not at the level of the best humans. It's average at best.
So you've never tried FSD.
The one that requires full-attention from the driver? No.
Depends what your definitions of "requires" and "full" are. On mine there's some nagging on the scale of once every tens to hundreds of seconds if it thinks I'm not paying attention. You're willingly living a more stressful and unsafe life if you're still manually driving your car in 2026.
Sounds less stressful.
sounds about right
> It’s informed by trend extrapolations, wargames, expert feedback, experience at OpenAI, and previous forecasting successes.
In other words: bias. Tons and tons of self-congratulatory, glue sniffing bias.
> Hacker News Guidelines
> Please don't post shallow dismissals, especially of other people's work. A good critical comment teaches us something.
At which point do we get to fight in the anti clanker uprising?
I wonder when the people will get that intelligence is not only directed at the external, but only really starts when you look at the internal (joy, pleasure, traumas, taboos, awkwardness, abuse etc.). Look up the word "interoception".