If AI is now ascending an economic learning curve from:
1. Extremely useful (Claude Code & Waymo now)
2. Doing ~everything we do (AGI & Optimus in a few years? 10?)
3. RSI (?)
4. Being smarter than any living person at every intellectual task (?)
5. Being smarter than the best-organized aggregate of all humans (10-100 years?)
...And all of the scientific and resource-allocation institutions that brought us the computer and the second half of the 20th century are now fixated on this learning curve, what universe can we possibly imagine where this is not transformative and powerful?
Honestly the only one I can think of is one in which we kill almost everyone in some other way first, and contrary to what you read in the news, almost everyone dying is not what the trend line has been from existing problems like war, disease, or even climate change.
Also, just to pre-empt a common quibble: when I say "AI" I mean the set of all AI and their combined decision vector, not any one AI, so conflicting interests within the set of AI's will not save anyone any more than the conflicting interests of colonizers saved indigenous Americans.
If (1) then somebody in the administration messed up badly. Glasswing has been a thing since April, and it's common knowledge that there would be some fuzzy edges around whatever restrictions a model has in place. There's no reason to let it launch and then pull it back.
(2) This "hype" meme is overrated. Enterprises (ones without a horse in the race, at least) will choose the model their best engineers ask for, or their competitors will lap them. I have been finding Codex more useful (even than Fable) but for a lot of tasks it seems that Claude Code is faster. This is one customer base where the general consensus here on HN is more influential than anything the Trump administration could do or anything Anthropic could say.
(3) "US government seems out to kill you" does not necessarily make valuation go up, and we've already seen this administration in an avoidable spat with Anthropic.
(4) This seems way less likely than a mix of (1) and (3) to me. The arguments for banning a useful technology to save jobs haven't really made sense since cars or indoor plumbing and don't get taken too seriously in either party at senior levels. That could change but it will take a lot for it to change.
The statement said that even foreign nationals within the US would be barred. That seems intentionally unworkable to me, and makes me think that the intent was to be more restrictive/disruptive than even an export control. It is hard to tell what the internal discussions are, but given the last run-in between the administration and Anthropic, and given the administration's politicization of nearly everything, I think it's likely that this is not necessarily a long term across-the-board policy plan.
I agree that it's really hard to tell from the outside, but if I had to guess I think we still have more to worry about on the side of "Wall Street races to superintelligence" than on the side of "KYC for AI". I could be wrong though.
I mean, if the stated intent of an export control is to allow domestic use but prevent export, achieving the stated intent is impossible, because every developer in the world wants the latest models and will get a VPN.
I think we should see this as simply silly behavior by a government.
Export control is not an effective tool for controlling a consumer facing technology developers everywhere want to use (see:VPNs) so there was no good faith policy justification for imposing an export control.
This is an administration that seems to be keeping track of who its friends are and aren't, and likes to be the center of every story. They also seem to like extracting concessions and reciprocal favors. We saw some of this behavior in the last administration too. US voters deserve better.
To make sure we keep track of what we're talking about with loss-of-control x-risk, a sufficiently smart version of Claude Code is more deadly than any government's army of autonomous killbots, because it can recursively self improve and has unpredictable training-induced preferences.
Exactly. And within the AI safety discourse, your behavior hinges on what you think the default chance of doom is, and how optimistic you are about alignment work being able to limit it before we reach superintelligence.
People running the labs are in a middle camp where they are scared enough by AI to take the threat seriously, but much more optimistic about alignment than the people who seem to have thought about it the most.
One major source of conflict in AI policy / AI safety is that very smart people have radically diverging intuitions about how dangerous superintelligence is and how difficult it is to align.
A first group dismisses the problem entirely, saying intelligence != power and AI doesn't have "drives".
A second group believes that alignment is solvable through engineering and iteration, and that we have the best chance of surviving if people with the right intentions are the ones working on it.
A third believes that aligning a superintelligence is a unique category of problem, that we are nowhere close to the level of scientific understanding needed to achieve it, that we only have one shot (because once a sufficiently powerful superintelligence exists it will thwart all future attempts, and alignment techniques that worked on dumber AI will likely not work on it), and that the world will have to coordinate to avoid killing ourselves off by building superintelligence before we understand how to do it safely, the way we have coordinated to avoid nuclear war.
The Anthropic and OpenAI founders, Elon, and Anthropic engineers are mostly in the second category. Some safety people at Anthropic and OAI are in the third category, but leading people in the third category think that pure safety roles at the labs are potentially impactful enough to be worth not quitting.
The idea that AI companies scaremonger to sell models is a silly meme.
Both OpenAI and Anthropic were founded by people who sincerely believed in the risk of out-of-control superintelligence. This is part of a clear historical record that is available for anyone to Google. Whether you agree or not, we have no reason to believe their statements about risks are insincere.
Reminded me of this post by EY. (You're making a different point about existing expertise, not LLM expertise, but I think it holds in general.)
Every month a new guy discovers LLMs; discovers a skill the current LLMs require to get good results; and writes about the future jobs that will always be available for smart people like HIM, that are SKILLED in using LLMs.
The next generation of AIs doesn't need his fancy prompt. The image model goes from needing to type in just the right set of weird words and cryptic sorcerous invocations, to most people being able to type in English what they want and get a pretty good result.
There are still tasks that require careful invocation. But they are a much smaller fraction of all the tasks people are trying to do, or you can get a bleh result without the elaborate invocation to get it really good. And to improve on the bleh result you need to be substantially more of an expert than back when the Guy was memorizing a rule about adding "trending on Artstation" to the image prompts, as would always require a human paid to do that.
Another generation of AIs comes out. The next generation of Clever Skills is obsolete. Image models just obey the instructions for compositing panels without mixing them up, and you don't need to be an expert to get them to do it right. Another human value-add is gone. A wider set of tasks require no human expert.
Now a new Guy notices LLMs have become useful in his field for the first time. He discovers they require SKILL to use CORRECTLY. He posts about how there will always be jobs for humans who are SKILLED in using LLMs like HIM.
But it is not an infinite cycle. It is not the same each time it repeats. Now the Guy is a highly paid programmer or a career mathematician in 2026, instead of a graphic artist in 2023.
In six months the models will no longer require his vaunted Skills.
And by then there will be another Guy.
But the process doesn't continue forever. The Guys are coming from fields that were harder and harder for AIs. The brief centaur eras are shorter and shorter.
Today it is writers who are laughing at how bad the LLMs are at their job, and who will perhaps soon be posting about how it takes Skill to get an LLM to do their job Correctly. But the models are coming faster, and the eras of kinds of human value-add in each field are shortening.
There is a point when you run out of Guys, either because the centaur eras are too short for people to develop SKILLs and post to Twitter about them; or because there are not lands left for AIs to conquer; or because ordinary people are not reassured by some Nobel laureate proclaiming there will always be jobs for Nobel laureates with the SKILLS to prompt robotized biology labs Correctly.
But we'll never run out of amateur economists who assert entirely without a brief contemporary example that there will always be jobs for humans skilled at operating AIs!
We'll run out of professional economists saying it when nobody is paid for that work anymore.
I guess we'll also run out of amateur economists when they're dead.
This was one of the rare critiques of AI doom that actually understands the case for it and presents them well, so I kept reading to see what its arguments for our safety against AI doom were. They were roughly:
1. It's hard to put a cat in a box despite us being smarter than a cat, so we're safe. (Counter: we're pretty good at putting cats in boxes when it matters.)
2. It was hard for Australia to kill Emus, so we're safe. (Counter: Australia could probably kill all Emus if it mattered enough, and we definitely accidentally kill off species when one of their inputs for life matters enough to us.)
3. Some smart humans get paralyzed by hedonism or existential angst instead of optimizing for arbitrary goals implied by their arbitrary value sets, so we're safe. (Counter: others overthrow the Czar, land rockets, etc.)
4. Modern AI is data-trained, so recursive improvement requires more data, so we're safe. (Counter: AI-crafted, synthetic data is a thing.)
5. We don't (yet) know how to improve our brains with brain surgery, so we're safe. (Counter: same as #4 above, which unlike us/evolution AI is being deliberately trained to understand and perform.)
6. Children take a long time to grow up, so we're safe. (Counter: the author's own "Premise 5: Computer-Like Time Scales", where they correctly note that computers can be arbitrarily faster than us.)
7. Individual smart humans on a desert island would be cooked, so we're safe. (Counter: nothing says the capability of a single AI must stop at that of an individual human, or that of a small group of smart humans; humans brains got dropped into a savannah and eventually they launch rockets.)
8. If AI doom is not a real threat, believing in it makes you believe some other not-real things that seem crazy or distasteful. (Counter: do we have a clear argument why it is not a real threat yet, in the list above?)
Within software engineering, security, reliability, and scale also seem boundless.
Software that never breaks (including because it never runs into scaling problems) and never leaks your data is preferable to software that breaks and leaks your data sometimes, but it has been too costly to be practical.
Current models are still very far from the reasoning muscle required to build things that never break, scale to billions of users with no issues, and cannot be exploited.
Good luck finding any objective distinction between HN, Reddit, WhatsApp, Signal, or email + listserv and "social media"!
Or finding any one of "social media's harms" that could not, in some world where Facebook, Instagram, and Tiktok did not exist, be delivered in just as socially harmful (and beneficial) a form by sufficiently-accessible versions of the apps and protocols you value and use every day.
I met someone recently whose primary addiction is Wikipedia.
For me, Signal and Hacker News are the most addictive pieces of software I still use.
Serial television (best delivered by WebTorrent and The Pirate Bay) is by far the most addictive, for me, so much so that I had to quit.
And you can definitely run successful social movements and political campaigns (for both very good and very bad things) over HN or WhatsApp/Signal, given sufficient adoption.