alt Hacker NewsTo grieve, or not to grieve?
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I am also an optimist about AI, although I worry about the labor aspect as well (as a leftist I see the class aspect of this, on the other hand, as a computer programmer, computers were also originally meant to replace human labor, and we all see what happened).
My view is, current top AIs do multiple different things:
1. Interpret and output natural language
2. Do formal logical reasoning
3. Do informal logical reasoning
4. Provide encyclopedic knowledge
5. Discern vague instructions/statements and fill the most likely gaps (kind of error correction)
6. Serve as a model of the human mind, a proxy for a person
7. Translate between different languages, formal and informal
All these things are combined in these huge, hard-to-understand blobs of weights. I think humanity would be better off by understanding each aspect separately, but disentangling them will take decades of philosophical research. So there is a lot of interesting work ahead of us.
I share the optimism here. Connecting dots across knowledge, lived experience and purpose remains, to me, a deeply human pursuit. The more AI discovers, the more possibilities we have to connect those discoveries to questions that matter to us.
> But do I “understand” the proof of Fermat’s Last Theorem, given that earlier this year I gave 22 hours worth of lectures on the topic?
Even if no one human can understand the entirety of a complex proof, surely we can piece together multiple experts' separate understandings, so the community as a whole 'understands' the proof?
Is there value in us 'understanding' a proof? Even if no single human can understand a complex proof soup-to-nuts, and we have to piece together several experts' understandings?
If the answer is Not really, then the value of a proof is its utility, its utility in making new products/services, and its utility in making new proofs. If in the case of abstract math, all the utility is of the latter kind (making new proofs), then we have a pyramid scheme here.
"if we get on board now then they will take us to extraordinary new places. And after we have arrived, the new adventure will begin"
This is the thought of an AI optimist and the one I share, new adventures, more tools, better results, and a never ending pool of ideas to work on
https://thebhc.org/node/97369 "The Decline and Fall of the Horse"
I argue that the Industrial revolution created 'unemployment' in beasts of yoke and burden at a larger scale than humans. So, there may be something instructive in that turn of events, even if it's not a highly representative analogue of the current ones. Of course, it's like saying what's a house cat to do when there's no more mice to hunt (assuming it remains fed). Maybe knowledge workers will become qualified pets if they prove cute enough.
My border collie will be pretty depressed though, once it's out of a job (maybe replaced by a drone sheep-herd).
Jev says: .78 grieve, .22 no_grieve
> Recent events in the field of AI for mathematics have shown us beyond all reasonable doubt that the field is currently undergoing a rapid transformation, unlike anything that we have ever seen before. Language models are solving hard problems which humans could not, and mathematicians are reacting very differently to this news.
Software I understand but could someone please bring me up to speed what's with Mathematics that it is being disrupted too?
Buzzard is such a good writer. Read it all the way to the end - it gets (even) better as it goes along.
As a non mathematician I think it could be kind of interesting to see what the AI can come up with.
Every time I read an AI article that uses the "stages of grief" analogy, I remember that Elisabeth Kübler-Ross, who created the model, said in an interview near the end of her life that anger was the only stage she personally felt.
Perhaps I'm missing it, but the "solving" of mathematics seems much more related to computational capacity growth and the development of Lean than necessarily advances in LLMs. Swap the LLM for an RNG and insert unlimited sampling. Don't we get the same result thanks to Lean?
or oppositely: to celebrate, or not to celebrate?
sounds like bargaining to me.
I've gone back and forth between "we're so cooked" and "we're so back" and I've started heading back to the latter.
I don't like programming with AI help. It still feels, at best, like playing Doom with cheatcodes on: it'll get you to the end, but you're not actually playing the game that way. At worst, it's like attempting to eat with soft silicone chopsticks: what the "tool" does is so removed from your intent and commands, and its feedback so delayed and sloppy, that you can only wield it in broad general strokes, not with precision.
But I'm encouraged by the hope that programming with regular tools like an IDE, compiler, debugger, etc. in a world with AI will become more like painting in a world of photography. Painting never died, but it had to change in a world where images of the real world could be captured without the skill or interpretation of an artist. The easy money in things like portraiture was gone (some people, including heads of state such as the British royal family and every U.S. president, still sit for paintings but it's far less common). Painters had to adapt and to do so they leaned hard into imagination, developing new styles and forms, new ways the art could be bent, and trying to show the world that though their skill and imagination was no longer needed to capture images of the real world now that photography existed, it still mattered.
That said, there is still a rich commercial market, even today, for more traditional forms of painting. Fantasy and science fiction novels need cover art. Movies, TV shows, and video games need concept art. Comics and animation productions need backgrounds. Even Bob Ross and his happy little trees taught us that there is joy and value inherent to the practice of painting itself, in creating peaceful worlds for our minds to inhabit. Painters who find some form of pecuniary success have it good today, because even for the ones who submit to commercialism, their capacity for imagination and originality become the selling point now that verisimilitude is a problem so solved, people carry collections of thousands of realistic images around on their phones.
There will emerge a market for code written by humans. This has to happen: I can't prove it, but I can feel it. Despite vast improvements in the generative models, AI-generated art and music are still slop. AI-generated prose has gotten sloppier with phenomena like the much-mocked "Claudese". It's so obviously devoid of a human mind behind it that Zoomers and Alphennials are starting to use "that's so AI" as an insult. Despite the leaps-and-bounds improvements of recent models, I have to believe that AI code is slop too; the major difference between code and these other expressive forms is that we are far more tolerant of slop code: for the most part we just care if the damn thing works.
But I think that will change. I am far more tolerant of poorer quality art, for instance, than I used to be if it were created by a human. It's almost an autonomic response: I see human-created art, I like it by default. Because I can glimpse the mind behind it in a way I just can't with AI slop. The ability to program a computer directly, and to combine that with imagination and originality to bend the machine in ways yet unthought of, will become valuable. There will emerge a qualitative difference between handmade code and slop code that people will notice and seek out. You will get some sense, however small, of who created the code by reading it, or interacting with it, and humans are far easier for humans to read and understand than machines running unseen, unfathomable stochastic models. It may well mean that the easy money in programming is gone forever. Perhaps people will continue to be content with slop for the vast majority of commercial code, and that's fine; they're welcome to it. This development will push us and our craft in a new direction. It's gonna suck, maybe for a few more years. But I'm starting to think maybe traditional programming is far from cooked. And who knows—maybe AI-induced brainrot, combined with model collapse and skyrocketing inference expenses, will mean that a bubble pop is coming and humans will have to pick up the pieces, potentially making a killing like COBOL programmers during the Y2K days. It's tough to say.
- they are not solving any hard problems
- https://www.technologyreview.com/2026/09/22/1144867/dont-be-... might wanna take a deep dive
It's much less the mechanism of AI than the potential policy implications.
That much concentrated data/compute is Checkov's Gun[0].
To assume we can find some policy lock for that gun is to believe the laws against murder preclude violence.
Most of these idealistic pieces about AI seem to come from senior, established or wealthy people who aren't very exposed to the labor market. In that view, the question of AI and its transformation is almost philosophical like this piece.
It's more a question of survival if you're labor though. It's very transformative tech but it's coming at a time when the scales are heavily tilted in favor of capital over labor, the government is the most corrupt its ever been and AI is going to make that much more extreme. It doesn't matter how amazing the technology is if all the benefits are going to accrue to the same few people who already have everything and destroy everyone else's bargaining power.
The shape of five stages of grief is something I see recurring in AI discourse. It also happened with programmers - they are currently at bargaining.
Some are still at denial. “It’s all hype like NFT and crypto, the bubble will pop soon”.
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In contrast to what these philosophical pieces tend to convey, the main crisis in mathematics is a labour one.
Mathematitians exchanged proofs for employment. That was the currency. Now they cannot use that currency anymore, so the question is how does someone know if they should hire an unknow person or not?
Philosophicaly who cares if you like more theory building or theorem proving? You dont need to convince anyone. The only solution is to be curious and follow your interests and naturally humanity will redefine what the new mathematics feels like.
You cannot convince anyone about it, its not something rational.