The domain has been mentioned on HN before (without TLS), this account seems to be just messing up the links (replace https with http to see the page)
soco 2 hours ago [-]
Computers are old tech nowadays...
claudiug 3 hours ago [-]
bullshit. you hear that you are not needed, you data is not yours. the AI lovers thinking: "humans also consume energy".
tqi 4 hours ago [-]
> The report estimates that training the latest frontier large language models, such as xAI’s Grok 4, can generate over 72,000 tons of carbon-equivalent emissions.
That seems pretty trivial, relative to 38bn per year globally?
azakai 2 hours ago [-]
Another way to put it: if training a model cost 72,000 tons of carbon, and it then gets used by 100 million people (typical of major models), the cost per person is 0.00072 tons.
Per the article, the average human uses over 5 tons per year (Americans: 18). Adding 0.00072 to 5 is not really noticeable.
(There is also the cost of inference, of course.)
jeffbee 3 hours ago [-]
Yeah it's basically nothing despite the fact that xAI seemed to intentionally crank up the carbon intensity for no reason.
Also, hilarious to select 2 major models from 2025 and they're both Grok, almost certainly the least useful, least used, and least interesting of that year.
amelius 8 hours ago [-]
Also nobody will ever have a moat, so the graph of investor stupidity is going through the roof.
aspenmartin 8 hours ago [-]
Of course they will. Tokens are valuable, you can always spend a finite budget on specialized tokens or fewer and higher quality tokens, size of user base and engagement gives you a flywheel moat that is difficult for newcomers to compete with. The market is complex and easy to oversimplify.
bryanrasmussen 8 hours ago [-]
My new startup tokencoin will blah blah blah exchange rate, (something AI writes here), 3. profit (more AI), benefiting all human kind and helping our users scale up their productive intelligence!
bryanlarsen 8 hours ago [-]
It's hard and complex to enter any mature market. The vast majority of firms that attempt to enter a new market fail. LLM's have no more than this normal moat.
aspenmartin 6 hours ago [-]
Well yes that’s my point: AI does not suddenly do away with the market.
bryanlarsen 54 minutes ago [-]
If every market has a moat, then saying that a particular market has a moat is a statement without meaning. The OP was probably not trying to make a meaningless statement, therefore the OP was probably saying that LLM's don't have an abnormally effective moat.
I agree, LLM's don't have an abnormally effective moat, just the standard moat most mature markets have due to market complexity. IOW, LLM's will likely end up with the standard oligopoly most modern western markets end up in, which have minor but relatively ineffective pricing power.
SilverElfin 7 hours ago [-]
Isn’t capital and momentum a moat? Sure Chinese models use distillation but I don’t see them training models from scratch. At least not today. But maybe as chips get cheaper and they have Chinese made ones?
swiftcoder 7 hours ago [-]
> Isn’t capital and momentum a moat?
Apparently not much of one. There are, what, 5 or more companies with frontier models? And open weights models like MiniMax are snapping at their heels
amelius 3 hours ago [-]
And it does not even consider that e.g. the EU might one day decide that AI should be for everyone, thus releasing a heavily subsidized open source model.
Or that at some point AI is good enough, and so at that point any model will do.
Nevermark 6 hours ago [-]
There are many markets where open source has been nipping at heels for a long time.
Obviously product areas differ for reasons structural and happenstance. But there is definitely a pattern that occurs, where open source fast follows commercial advances, benefiting from having a clear target to develop for.
Which is of course, a great service. Even if it never unseats the commercial version, it forces the owners to reinvest more in improvements, by undermining their moats. As well as providing a much better value alternative version for many people.
SilverElfin 7 hours ago [-]
I’m not technically familiar but I remember someone saying that models like MiniMax basically skip the cost of training by using distillation to basically “steal” the models from OpenAI or Anthropic, and that these companies now have various defenses against this. What happens when MiniMax has to do the full work themselves?
lelanthran 3 hours ago [-]
Why would they have to do it themselves?
bossyTeacher 7 hours ago [-]
>Chinese models use distillation but I don’t see them training models from scratch
Maybe because they don't have to. If someone is doing the heavy work and they can take output of that, it's a win for them.
xnx 7 hours ago [-]
The "China leads in robotics" seems to be unaffected by AI. The China line is basically on the same trajectory since 2012. The chart does no belong in the article.
cloud-oak 7 hours ago [-]
> Training AI models can generate enormous carbon emissions
Sure, but what I'd really like to see is a graph for how much carbon is generated serving these models globally.
hydrocomplete 8 hours ago [-]
I still don't understand the State of AI in 2026.
i_love_retros 5 hours ago [-]
Stating "Software engineers are all-in on AI" because of an increase in github projects being created is hilarious. I didn't realise creating a github repo made someone a software engineer. If only I had known this I wouldn't have bothered learning all the other stuff!
gregsadetsky 3 hours ago [-]
I agree with you on that metric being not great - I would have definitely swapped it for this:
Sure - also an imperfect metric. But less imperfect? And more indicative of... something? Not nothing?
HelloMcFly 7 hours ago [-]
Besides the lead in robotics for China, those Grok emissions charts are the thing that most leap off the page.
xnx 7 hours ago [-]
"These estimates should be interpreted with caution. In the case of Grok, they rely heavily on inferred inputs drawn from public reporting"
That chart doesn't really pass the sniff test.
HelloMcFly 6 hours ago [-]
The rest of the quote you began continues:
"On the other hand, Perrault noted that 'Epoch AI independently estimates Grok 4’s emissions to be significantly higher at approximately 140,000 tons of CO₂.'"
I realize these are still estimates, but when the other independent analysis nearly doubles the outcome I'm not left feeling optimistic. One could argue some numbers from others are underestimates... which of course just bums me out all the more!
jazzypants 6 hours ago [-]
I don't know if I would want to do too much sniffing around the Methane power they are using over at xAI.
That's definitely a very visible use of carbon generating fuel, but I'd choose methane over coal power plants all day.
jazzypants 6 hours ago [-]
I agree 100% if those are the only two options. I guess my point is that it's fair to assume that Elon's crew is doing the bare minimum in terms of efficiency and pollutant mitigation-- at least when compared to other data centers who do legally compliant business with real power companies.
themafia 6 hours ago [-]
Profits generated by AI: <not graphed>
The absence speaks volumes.
johnnienaked 9 minutes ago [-]
There hasn't been one dollar of profit from any company, it's more a battle of how low you can keep your losses
bix6 7 hours ago [-]
China’s robotics lead holy cow.
signatoremo 5 hours ago [-]
That's the lead in industrial robot installed. That lead is understandable because of manufacturing concentration in China. Here are 10 top robot makers, none of them are Chinese (*), and five are Japanese:
(*) Kuka was a top German maker who got acquired by Chinese company Midea recently
bsza 5 hours ago [-]
They also lead the world in EV production on paper, but in practice a large portion of those numbers might be driven by government pressure, not actual demand [1].
I’d personally take this data with a big grain of Goodhart’s law.
The graph says "new industrial robots installed", which is a bit misleading. For example the newest BYD factories are still stuffed with German/Japanese robots.
alex43578 7 hours ago [-]
China’s manufacturing lead in a graph
xnx 7 hours ago [-]
It striking, but says nothing about AI.
ranger_danger 7 hours ago [-]
Don't they have ten times more people than the next highest country (Japan) though?
Teever 6 hours ago [-]
What's worse is that this the predictable result of a choice that America made decades ago and continues to make.
Outsourcing manufacturing capacity to China and letting domestic manufacturing skills atrophy and institutional knowledge die out was a choice that many people opposed but were ultimately helpless to stop because the people making the decisions ignored them and did it anyways for personal gain is how we got here.
You'd think that the supply chain shocks that we saw during COVID would be a wake up call that would have jolted people into action.
You'd think that Ukraine-Russia war would have been a wake up call that would have jolted people into action.
You'd think that the recent failures by the US military in Iran and the depletion of years of missile stockpiles would have been a wake up call that would have jolted people into action.
I'm at a loss to explain it. It's like the American oligarchs want to weaken America, or at least are willing to do so if it means that they have greater control over it. Maybe they don't care about manufacturing capacity because they know that America is ultimately a nuclear protected island and that even if things continue to decline they'll be safe to rule it like a king?
Tanoc 3 hours ago [-]
> It's like the American oligarchs want to weaken America, or at least are willing to do so if it means that they have greater control over it.
The capital holders want it under their control. The fact that it harms the state is a consequence they ignore, or worse, believe that other people will deal with. There is not thought given to how much harm will be caused, because the harm is seen as part of the process used to acquire that control. It's the sort of thinking that aligns with beating a dog to teach it not to bark and then ignoring the cataracts that form from the repeated blows.
bauerd 7 hours ago [-]
[dead]
eulgro 5 hours ago [-]
> The report estimates that carbon emissions from models with the least efficient inference are over 10 times as high as those with the most efficient inference. DeepSeek’s V3 models were estimated to consume around 23 watts when responding to a “medium-length” prompt, while Claude 4 Opus was estimated to consume about 5 watts.
This makes absolutely no sense. I suppose they meant watt hours, and that's a weird way to explain carbon emissions...
cause up until now I have observed the exact opposite which is coherent with expectations: https://coding2learn.org/blog/2013/07/29/kids-cant-use-compu...
archive.today suggests, there's never been (The only https returns 403 in 2015, the 2013 links are http) https://archive.is/https://coding2learn.org/
The domain has been mentioned on HN before (without TLS), this account seems to be just messing up the links (replace https with http to see the page)
That seems pretty trivial, relative to 38bn per year globally?
Per the article, the average human uses over 5 tons per year (Americans: 18). Adding 0.00072 to 5 is not really noticeable.
(There is also the cost of inference, of course.)
Also, hilarious to select 2 major models from 2025 and they're both Grok, almost certainly the least useful, least used, and least interesting of that year.
I agree, LLM's don't have an abnormally effective moat, just the standard moat most mature markets have due to market complexity. IOW, LLM's will likely end up with the standard oligopoly most modern western markets end up in, which have minor but relatively ineffective pricing power.
Apparently not much of one. There are, what, 5 or more companies with frontier models? And open weights models like MiniMax are snapping at their heels
Or that at some point AI is good enough, and so at that point any model will do.
Obviously product areas differ for reasons structural and happenstance. But there is definitely a pattern that occurs, where open source fast follows commercial advances, benefiting from having a clear target to develop for.
Which is of course, a great service. Even if it never unseats the commercial version, it forces the owners to reinvest more in improvements, by undermining their moats. As well as providing a much better value alternative version for many people.
Maybe because they don't have to. If someone is doing the heavy work and they can take output of that, it's a win for them.
Sure, but what I'd really like to see is a graph for how much carbon is generated serving these models globally.
"Claude Code GitHub Commits Over Time" https://newsletter.semianalysis.com/p/claude-code-is-the-inf...
Sure - also an imperfect metric. But less imperfect? And more indicative of... something? Not nothing?
That chart doesn't really pass the sniff test.
"On the other hand, Perrault noted that 'Epoch AI independently estimates Grok 4’s emissions to be significantly higher at approximately 140,000 tons of CO₂.'"
I realize these are still estimates, but when the other independent analysis nearly doubles the outcome I'm not left feeling optimistic. One could argue some numbers from others are underestimates... which of course just bums me out all the more!
https://www.theguardian.com/us-news/2025/jul/03/elon-musk-xa...
The absence speaks volumes.
https://manufacturingdigital.com/top10/top-10-industrial-rob...
(*) Kuka was a top German maker who got acquired by Chinese company Midea recently
I’d personally take this data with a big grain of Goodhart’s law.
[1]: https://www.bloomberg.com/features/2023-china-ev-graveyards/
Outsourcing manufacturing capacity to China and letting domestic manufacturing skills atrophy and institutional knowledge die out was a choice that many people opposed but were ultimately helpless to stop because the people making the decisions ignored them and did it anyways for personal gain is how we got here.
You'd think that the supply chain shocks that we saw during COVID would be a wake up call that would have jolted people into action.
You'd think that Ukraine-Russia war would have been a wake up call that would have jolted people into action.
You'd think that the recent failures by the US military in Iran and the depletion of years of missile stockpiles would have been a wake up call that would have jolted people into action.
I'm at a loss to explain it. It's like the American oligarchs want to weaken America, or at least are willing to do so if it means that they have greater control over it. Maybe they don't care about manufacturing capacity because they know that America is ultimately a nuclear protected island and that even if things continue to decline they'll be safe to rule it like a king?
The capital holders want it under their control. The fact that it harms the state is a consequence they ignore, or worse, believe that other people will deal with. There is not thought given to how much harm will be caused, because the harm is seen as part of the process used to acquire that control. It's the sort of thinking that aligns with beating a dog to teach it not to bark and then ignoring the cataracts that form from the repeated blows.
This makes absolutely no sense. I suppose they meant watt hours, and that's a weird way to explain carbon emissions...
https://news.ycombinator.com/item?id=47758028
Source: https://hai.stanford.edu/ai-index/2026-ai-index-report