Graphs that explain the state of AI in 2026
spectrum.ieee.org
spectrum.ieee.org
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)
I don't see that.
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...
They know how to navigate through the intricate settings of their favourite social app but debugging connection issues is too much (even on a very basic level, "can my browser access the same site?").
"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 seems pretty trivial, relative to 38bn per year globally?
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.
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.)
That does not cover the whole usage: the hardware, the bots that collect learning data, the prompts, etc. And there are now many models of this size, and thousands and thousands at smaller sizes. And some of this parameters are increasing.
AI is estimated to emit more than 80e6 tons of CO2-equivalent this year. Much more than whole countries like Austria or Israel. Is that trivial?
These numbers keep being put up as large in absolute terms but that’s deceiving for the average person who doesn’t have a way to compare them to something relevant in their lives.
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
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.
Or that at some point AI is good enough, and so at that point any model will do.
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.
This makes absolutely no sense. I suppose they meant watt hours, and that's a weird way to explain carbon emissions...
That chart doesn't really pass the sniff test.
https://www.theguardian.com/us-news/2025/jul/03/elon-musk-xa...
"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!
Sure, but what I'd really like to see is a graph for how much carbon is generated serving these models globally.
The absence speaks volumes.
errr… no? Every discipline is clearly hitting a plateau so far. Some started recently and hence haven’t yet (competition maths) but based on past graph, they will all plateau.
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.
I’d personally take this data with a big grain of Goodhart’s law.
[1]: https://www.bloomberg.com/features/2023-china-ev-graveyards/
https://manufacturingdigital.com/top10/top-10-industrial-rob...
(*) Kuka was a top German maker who got acquired by Chinese company Midea recently