I think beyond the specific elements of any domain AI eclipses humans in, overall, the notion of the thing that grants you status, prestige, and a living wage being commodified would spark in anyone a profound sense of dread.
Beyond just making you redundant in your job, the whole architecture of your existence, the thousands of hours of struggle, the sacrifice of putting off social games or personal enjoyment are now rendered moot in hindsight. You are made one step closer to complete worthlessness, which will surely continue as AI becomes a more satisfying personal companion, a more worthwhile friend, lover, etc.
How is one to feel safe in the progress of the future when the only hints of the wonderful post-scarcity utopia we can quantify so far is the removal of all human leverage via their labor? All it tells us is we will be bargaining with superintelligence with nothing to stand on, only a trust that the 5000 lab executives and researchers solved the most important research problem of all time on the first try.
And remember, these AI models were trained on your work, your culmination of effort and sacrifice, without any consent, credit, or compensation, then sold back to you for a subscription fee.
> You are made one step closer to complete worthlessness, which will surely continue as AI becomes a more satisfying personal companion, a more worthwhile friend, lover, etc.
I recently thought about this and fear that AI may further drive us humans apart.
Instead of working with humans, I increasingly work with a fleet of agents.
> the notion of the thing that grants you status, prestige, and a living wage being commodified would spark in anyone a profound sense of dread.
Not for those without status (which is most people on this planet). But yes, AI is set to wipe out most established hierarchies and their gatekeepers, and to equalize most fields. A profound sense of dread is something most ordinary people live with throughout life, and if AI can reduce systemic unfairness, I bet most people will actually find some degree of relief from that dread. The complacency of the formerly-statused being shocked along the way isn't much of an argument against that equalization.
> Beyond just making you redundant in your job, the whole architecture of your existence, the thousands of hours of struggle, the sacrifice of putting off social games or personal enjoyment are now rendered moot in hindsight.
This passage answers itself, doesn't it? You can sense those things you postponed fun for (work and the apparatus around its struggle) were never worth it. So why fight for us all to have to keep working just to live? Isn't a post-scarcity world the thing we should all be fighting for?
It's more or less reverse to the mean. The period in which a people had both access to education and leverage through their labor and intellect is super short. For most of recorded history, the bulk of humanity lived as peasants, serfs, or slaves. They were mostly illiterate, bound to the land or to a master, and had little power to bargain over the terms of their (or their children) lives.
Unfortunately, I think this is a human failing being exposed rather than anything else. We like to build conceptual models of how things work, but they are often tinged with should. Reality doesn't care how things should work. It only cares about how things do work. It's always jarring when the should turns out to be false.
Philosophers for millenia believed that human beings had meaning, purpose and set out to explore what that could be. It was a noble profession for a long time. Once we realized that there was no hidden spark, ergo no purpose, the study of and the prestige associated with philosophy took a nosedive. Yes it is still studied but it carries nowhere near the respect it once did. Mathematics seems to be suffering the same fate.
I think the fix is to get started on post scarcity economics now. Sooner or later we're going to have to come up with practices that boost or limit endeavors based on how people feel about them, rather than based on how much money somebody has.
It doesn't have to be ((post scarcity) economics), it can be (post (scarcity economics)). Both systems can coexist for a while, one providing a bit of a safety net while the other falls apart.
Counter point: AI is trained on output from humans. We all made AI, together. It belongs to all of us. We use it to benefit us, and we celebrate our wins together.
It's mainly about status. No one cares that much about AI automating drug discovery or coding, but it's bad when it assists in math. Math results are attached to individuals , whereas for cancer drugs or other medical discoveries, it's more of a team effort by a lab. AI now has the effect of turning math into something that is more lab-like and less about the individual.
Yes, and I think over time there will be a blatant inequality in who is commoditized and who isn’t.
If AI engineers didn’t create the data to produce the models, and they increasingly don’t write the code to produce the models either, then why are they treated as the agents of change rather than the subjects of change, like mathematicians are?
When I was a kid I built my entire identity around being #1. I was the most talented kid in school, anything endangering that resulted in an instant identity crisis.
Then I went to college and I understood that there are people who, for one reason or another, are thinking in ways so advanced I'll never catch up. I'll never be the #1. I'm actually much closer to being average than I thought.
But this doesn't mean I should just give up, lie down in my bed and cry. Since then I've learned a lot of skills - most of them being crap at best, but that's not the point. What matters is my own subjective experience. The fact that despite objectively not being good, I see myself as a skilled person with rich life.
Once I was watching a YouTube video about elderly care and there was a phrase along "These people won't achieve anything more in their lives, my goal is to keep them occupied until they die" which is a bit morbid at first glance, but it actually makes so much sense as a life philosophy.
I would answer to this that the mathematicians (humans) are the ones who give any meaning to mathematical discoveries. If we don't have mathematicians anymore, the result is that AI can find whatever they want, but 99% of that will be useless waste. Outside of practical applications, the only reason most mathematical results have any interest is that lots of mathematicians spend time trying to find their solution. Once humans stop caring, mathematics done in an automated fashion will also stop having any value, other than its possible use in finding solutions to existing engineering problems.
This part is nonsense, still. There's no known AI -> AGI path, and superintelligence doesn't mean anything, and AGI is assumed to be (going to be) both malicious and a slave, both for no good reason.
Nah. There is nothing beyond being made redundant in your job and labor leverage. That is all. It has got nothing to do with resentment over fucking machines. It’s all about people (the executives that you mention) fucking us over. The end. Completely human problem.
I know I’m being sold some bullshit when this is made into something inherently existential and psycho-identitarian. An egalitarian future of labor-worthlessness means that there is nothing above us to dictate anything at all—maybe not even nature itself, save for meteors and other cosmic events. I’m not afraid of being “worthless” in that world of complete freedom. Fuck no.
Consider this… in the grand scheme of things, we are on a tiny planet in the universe. What cosmic contribution could you make?
Most people won’t make anything even close to “a ding in the universe”, as Steve Jobs has been reported to say.
So they may as well enjoy their life. And your worth can be to your family, to your children, your parents who took care of you.
Learning a hobby. Practicing religion. Mindfulness and meditation. Doing sports and improving your own body.
Look around if you are a heterosexual man, for instance: many women are far more attracted to men that perform in the moment, than men who labor quietly to create a product. The former enables untold hours of honing social skills and calibration, and humor and performance skills. The latter is of more durable value to society, yet relatively few women are genuinely sexually attracted to a man doing the deep work. (By the way, it is also true the other way: most men are not attracted to women for doing deep work or being a rocket scientist.)
Animals don’t do “deep work” and most animals are attracted for far “shallower” reasons. If everyone has a UBI and AI does the “deep work” then that frees up humans to be like animals in a zoo or in the wild… doing all the displays to attract mates, having babies etc. That’s not nothing — in fact it is 99.999% of everything that happened in history and 100% of what happened in prehistory.
You’re just ceding that 0.0001% which represents technological progress. The actual dread comes from the fact that you and all of humanity will be as completely powerless to change things as cats or any random animal species is powerless now. The difference is you will perhaps understand your powerlessness more than they do. But in the good scenario, you’ll be like animals in a zoo. We are constructing this zoo for ourselves now.
We will remain on this blue planet while the AIs will colonize the universe. In fact I wonder why aliens would ever come to Earth, when they’d just send their AIs or robots. Look at this: https://news.ycombinator.com/item?id=46200502
For me the most obvious conclusion is, use your maths skills and get into open source AI.
Make AI as cheap and accessible to as many people as possible and we will likely be much better off.
The more people empowered by the tech the less like you will be “redundant” in the way you describe. You will own the important tools only the techno oligarchy own today…
Would you feel the same if you were a part owner of OpenAI? I bet you’d feel excited about the money you’re about to make ?
> How is one to feel safe in the progress of the future when the only hints of the wonderful post-scarcity utopia we can quantify so far is the removal of all human leverage via their labor?
I'm sure the Telegraph operators, human calculators, mine workers and all sorts of people have asked themselves this question. It's obvious that it feels strange to suddenly be part of the cohort asking but I assure you it's not new. And the answer hasn't changed much since.
> the removal of all human leverage via their labor
I’m not convinced at all that SI will ever be able to produce the correct result with little input. The advancements in capability I’ve seen in models is that they understand my intention better, and follow industry best practices better, so their output is often acceptable. But I absolutely have to make my intentions known, as detailed as possible, or I will get the mediocre, standard solution that falls out of the weights.
I’ve been having trouble with models always steering towards certain solutions - they insert a queue here, a mutex there, a backoff over there. If I remove those, and let the model freely rebase the PR stack, then it will re-insert those mechanisms because it has been specifically trained to do exactly that. It’s essentially boilerplate, smoothly aligning my codebase to match their weights. Which is often good enough! They are training the models well. But individual problems require individual solutions.
My personal take on the human part in all this is: We get to decide, and the models obey. Our decisions are now super leveraged. So let’s make good decisions, and communicate them well. The layer of where decisions yield the most leverage, has been pushed upwards (I see it on the type and function signature level, others will see it even higher), but IMO it won’t be possible to push it up much further without losing truth to the decisions we need to make for a good product.
I can kind of relate but I feel like I am mourning something different: the loss of the desire to seek truth in tech, math etc.
Nothing is validated or tested anymore. It’s all about the shape or believability or even how loud it is.
They dropped 100+ papers no one read. I am sure mathematicians are reading them now but even this forum has concluded that these problems are solved, without reading or validating.
It’s like everyone forgot “don’t believe everything you read on the Internet.” And it makes for a very boring discussion when everyone is just spewing unvalidated claims, layering them with strong beliefs founded on similarly unvalidated claims. It’s dull, without substance and just pure noise.
> I feel like I am mourning something different: the loss of the desire to seek truth in tech, math etc.
This is what I've been feeling too. It feels increasingly like the professional world has become a tower of scams. It's not worth building technical skills or focusing on quality; your boss doesn't know or care what good work looks like, he/she just wants your work to look good enough to his/her boss, who knows even less about the actual work being performed. And everyone reports up to an MBA CEO who was brought in from a completely different industry.
I want to work in an industry where skill, diligence and expertise is rewarded and respected, but from what I'm seeing political ability is 95% of the game and caring too much about the work is a career liability.
Not sure I agree - they dropped hundreds of papers, most of which were so badly written that they were incomprehensible. If it wasn’t for the lean certificates on 30% of them, the mathematical community would have told them to go and whistle.
I think the consensus here is that most of the papers are effectively correct. But it would take years of study just to understand most of the problem statement - so we have to wait for the mathematical community to digest the borderline-nonsense that OpenAI spewed out.
This piece circles, without naming it, around the concept of “deontic scorekeeping” central to the work of Robert Brandom on semantics. The idea that our ability to create and sustain conceptual systems depends on the give and take of reasons within a social setting. Brandom has been front of mind for me lately because elements of his theory both explain why LLMs should work in principle, and where they are bound to be radically deficient. An LLM encodes the normative regularities of our linguistic/conceptual games into its weights, but it cannot be a real participant in our games because it is incapable of staking durable commitments or changing its dispositions over time.
Worth reading: Robert Brandom, “Making It Explicit: Reasoning, Representing, and Discursive Commitment”
What a coincidence, I've also picked up inferentialism but never really got into it.
I'm interested in the reversal that Sellars proposes - it seems clear to me that "representation" is not prior to the space of reasons, despite how unintuitive it is.
> An LLM encodes the normative regularities of our linguistic/conceptual games into its weights, but it cannot be a real participant in our games because it is incapable of staking durable commitments or changing its dispositions over time.
I see no reason why this can't be the case in the future, even though I think inferentialist-based theories are generally strong. Can't you force LLM's (or whatever AI architecture will exist in a decade) to stake durable commitments itself, then? They're at least autonomous enough to run computers. I agree that that is a core part to true meaning & autonomy, but nobody just lets them yet. I don't think inferentialism is a consciousness-based argument, either, so that escape hatch isn't available. I also don't think this is a necessary condition to engage in the space of reasons (but maybe then I'm misunderstanding it, or retreating to a more Sellarsian understanding). Could you explain on this more?
Though again, I only have the book sitting on my desk, and I haven't cracked it open...
I think in future, each company will built its own universe of mathematics consisting of prized discoveries. Maybe one Mathematical Universe per Company in the multiverse of mathematics.
I think for me is, that history is not kind to the people who are left behind.
For example, weavers were one of the most powerful professions (if thats a thing) in the middle ages. In england there are the wool churches(not entirely weavers....), in the low countries, the weavers guild fomented revolutions, and shaped the borders of countries.
But that came to a crashing halt over the space of 200 years. slowly at first, then all at once. the power loom, then cheap imports from india turned a cottage industry into dark satanic mills. Yes there are/were specialists that still hang on, but they are like football stars you can probably name all the people who make money, the rest are barely scraping by.
For us, in the programming world, we will not have a 200 year grace period. Yes, AI produces shit code, but thats not the point. its cheaper and there are vanishingly small places were "good" code matters anymore. AI could be used to help a large range of people, provide support, trusted advice.
However because of the people who are funding it, that will not be the case. it will be used to reduce wages. Just like offshoring, resulting in china being the worlds manufacturing hub, AI, and the current people funding it will aim to make the expensive worker redundant.
In short, I weep, because Altman, and the money behind him ans his ilk want me destitute. I have committed the crime of wanting to earn a wage, and thus I must be punished.
It's profit chasing as well as practical - it kneecaps the educated workers increasingly asking questions about the morality of business and technology. It takes away the income that affords them the space to push back, threatens high ed, critical thinking. The salivating over AI makes perfect sense in that context.
I think Thompson has no understanding of endeavors like pure math or the theoretical sciences. In the words of Einstein, "I want to know how God created this world. I am not interested in this or that phenomenon, in the spectrum of this or that element. I want to know his thoughts; the rest [is] just details."
I think mathematicians aren't bemoaning their lost sunk costs. They're now aware that they may never again have the joy of being the first to pull up the edge of the tarp of ignorance and see the raw truth beneath _for the first time_. Their voyages of discovery, which give life meaning, may never leave dry dock again.
It is strange, because in a sense, when you start learning math, you never explore, you are being taught.
Now mathematicians were able to exercise curiosity. That is going to change. Back to the ranks of eternal learners if you will.
The fun was in the research. Now I think it will leave the door open toward more Applied math. What can people do with all the discoveries. The curiosity will be there.
I think it is better that way.
It will also put a cap on abstractions that overlaps. In essence, AI is less likely to create new theories, coin new terminology, etc. But it is better suited to recognize emerging patterns.
That will probably simplify mathematics.
Unless the domain of abstraction is infinite and with each new abstraction comes its own results but I doubt it. Who knows though...
> they may never again have the joy of being the first to pull up the edge of the tarp of ignorance and see the raw truth beneath _for the first time_
Until we can demonstrate AI consciousness, “seeing the raw truth” will be a human activity. Even now, verifying and understanding these AI proofs is a massive endeavor. Coming up with an intuitive (to humans) distillation of the finding remains an open challenging demanding expertise.
That's such a nice way to put it! I recently stumbled into "The Last First- Winter K2"[1] and saw the same spirit along with a similar misguided effort to win without the will, nor capacity to do it — e.g. influencers taking a stab at K2 is like prompting your way to results.
Why is not like changing to a different type of vessel for the voyage? Unless and until it is all AI in closed system, could direct machines where to look etc.
I'll say it again: AI is capable of answering the questions put to it but AI is not yet capable of knowing which questions are worth asking. Mathematicians have no cause to weep, they will be fine.
> The story of human discovery and the triumph of the human spirit will soon be excised from this discipline. The Dinitz-Garg-Goemans counterexample was the most egregious demonstration. It revealed that the process of prompting novel proofs will be as auraless as ordering doordash. Watch as magic and mystery evaporate. Watch as the sun sets on our heroic age. Is there not something evil in the act of blocking all future generations of mathematicians from the experience of discovery? Forget about accuracy or even attribution. Something fundamental to the experience of mathematics is being taken.
> You are a helpless onlooker. Before you a channel through which humans have accessed the ineffable and sacred for thousands of years is being sealed for eternity.
> They're now aware that they may never again have the joy of being the first to pull up the edge of the tarp of ignorance...
Not "never again", it would be extremely difficult but science and math are also built on random, trial and error, and intuitions that could not arise from AI.
> “Google Translate is amazing, but it has taught us essentially nothing about linguistics,” Strogatz said. “We don’t understand why it works. It just works. That’s the Twilight Zone. It is knowledge without understanding.”
This is not true, and it is the crux of an enormous debate we're now having across many, many fields.
Classical Chomskyan syntax (which models sentences as parse trees) has been enormously, astonishingly predictive of the rich structure in real-world human language. But we are quick to forget that we invented concepts like "words" and "noun phrases" specifically to help us analyze and predict things about human language. What LLMs and modern MT shows, definitively, is that there is another, totally separate way to describe these phenomena, which is both vastly less descriptive, and also vastly more predictive.
That these appear to trade-off is unfortunate, but it is NOT the case that we "don't understand why it works." We absolutely understand why it works, if we didn't understand we would not be able to improve these systems. What we do not have is a clean, descriptive theory that boils this down to something that is formally specifiable and analyzable. But those are different things, and this is the root of the disconnect between many communities working in and around these spaces (linguists vs computational linguists; mathematicians vs computational mathematicians; mech interp people vs empiricists).
"We absolutely understand why it works, if we didn't understand we would not be able to improve these systems" - Understanding how to improve something does not require understanding how it works.
Growing a plant does not imply understanding soil minerals or photosynthesis.
Training a dog does not imply understanding it's brain.
Using LLMs to improve a codebase does not imply understanding C++.
Improving a PC with new parts, does not imply understanding RAM.
You can understand abstractions about the system, without understanding the system.
Without gradient descent or other forms of automatic optimisation, do you think humans could build something as capable as GPT-1?
I think they're referring to the fact that neural networks are more or less black boxes. Their internals are blurry and not explainable in the same way that traditional linguistics tries to explain things - with rules.
Of course, ultimately that's because language itself doesn't follow simple rules like linguists would prefer. They're more like guidelines.
I still think mathematicians are going to be as important as ever. The LLMs are only finding what was technically possible given our current breadth of knowledge after brute force solving problems. Eventually it will run out of things that it can do with its training and the only way to get it to do more will be training it on new human found knowledge.
Finding that new knowledge may be exponentially more difficult, but it will be much more valuable.
> Eventually it will run out of things that it can do with its training and the only way to get it to do more will be training it on new human found knowledge.
Came here to say this. What AI is doing with math is essentially fuzzing, but looking for valid inputs that solve a problem and the inputs are mathematical abstractions. It's a cool approach, but AI doesn't understand what's going on, and without understanding it won't be able to create the next generation of mathematical abstractions needed for the next generation of proofs.
aren't mathematicians needed to create the problems? Everything solved so far is a question posed by a human. Which is probably why cracking diseases is more difficult (apart from man made viruses :/)
As a software engineer it is hard for me to feel sorry for these mathematicians. Software engineers are getting laid off because of advancements made by AI. Math researchers are employed at universities, and universities aren't laying off mathematicians now that OpenAI has solved some of their puzzles. Mathematicians can still feed their families, software engineers displaced by AI can't. Yet I see far more of these blogs about the plight of mathematicians, not enough about the plight of software engineers.
When software engineers spent the last 50 years eliminating the work of clerical, secretarial, and dozens of other back-office functions, were they concerned about how those people would feed their families? Do you think anybody but other software engineers feels any sorrow for them today, now that they are facing the same fate?
There are orders of magnitude fewer mathematicians with full time academic positions than there are software engineers. The economics are different and consequently academia tends to be more slow moving in reacting to market trends. It doesn't mean it isn't coming, but it will look somewhat different
I don't personally grieve for the likes of Strogatz or Tao, it seems likely both of them will be fine however this pans out. But many more mathematicians have been toiling away in precarity and obscurity and without tenure for years and years. And of course many mathematicians went into private sector roles as software engineers, actuaries, analysts, ML engineers and similar, and have been displaced there, too.
And highly visible blog posts written by famous mathematicians with large audiences and closely aligned with the news and hype cycles getting frontpaged on HN doesn't mean that mathematicians are disproportionately whiney, nor that software engineers aren't also writing about their plight or ending up on the front page as well.
To me this goes in the same direction as people not feeling sorry for software developers because our job is supposedly automating the job of other people (which I don't think describes the profession accurately as a whole at all).
Neither sits right with me. Can't we just all collectively acknowledge that we have to grapple with this new piece of technology that either is already or at least seems to be going to be hurtful to a lot of individuals?
Instead of looking at the in comparison limited group of people currently pushing this technology and asking ourselves whether we should be on board with their doing, we look to one another and are happy that someone else is now suffering just the same as we are. What a sad state of affairs.
As a software engineer? The career whose very reason, largely, for existing in this market is to automate jobs, with few notable exceptions? That one is somehow deserving of sympathy and that of mathematicians is not? Come off it. The notion is undignified.
> Software engineers are getting laid off because of advancements made by AI.
The bean counters laying off software engineers ought to take notes from the frontier labs' own hiring practices. They're still hiring lots of humans for business and engineering roles even when they would be better positioned than anyone to automate away those jobs with their world-class models (https://openai.com/careers/search/).
It's not about universities, it's about grant funding over the next few years. It is very apt to collapse if AI is more useful than people. Why pay people to find this when tokens will do instead.
It’s only been a few months since LLMs started solving significant open problems in math. I wouldn’t jump to the conclusion that they have it better than software engineers.
In many ways it will likely be the opposite. Tech firms still need engineers to talk to customers and run experiments. What will the mathematicians be needed for?
Software engineers are getting laid off because of the end of zero interest rates, wars started by Putin and Trump, and a bit because of pandemic over hiring. The part that is due to AI is less hiring of juniors. Know your enemy before starting a fight.
What's your source for "Software engineers are getting laid off because of advancements made by AI". I haven't experienced that in my field and can't find any data to support that notion.
> Software engineers are getting laid off because of advancements made by AI.
This is said by a lot of CEOs trying to make layoffs look good, but I haven’t seen anything that suggests that it’s true.
> Yet I see far more of these blogs about the plight of mathematicians, not enough about the plight of software engineers.
Really?!? We’ve been living through 3 years of blog posts, LinkedIn hot takes, and podcasts talking about the plight of software engineers in the era of AI. There isn’t a week that goes by without an HN post about it.
I can feel empathy for the practitioners in a field that may have been profoundly changed, the same way I can feel empathy toward software engineers who are struggling with the changes in their own field.
In the end, we’re all trying to figure out where this leads. And how this will affect our lives and our work.
Unless this is satire, have you not considered how many proles have been laid off because they were replaced by technology or told that a spreadsheet model had decided their job was superfluous? Capitalism has been using technology to fond new ways to enrich itself for the whole age of personal computing, and arguably long before. Those Andreesen Horowitz comments about 'software eating the world' may have been exciting to people working at startups, but came off as rather sinister to people who were in the world outside softwareand just wanted to build a modest but comfortable life rather than develop unicorns and cash out.
The difference is it takes great intelligence to be a mathematician, whereas anyone can be trained to write code. It’s like the difference between an automotive engineer and a mechanic. I would argue writing code takes less skill than carpentry.
Oxytocin is one of the oldest molecules in the world — it created sexual reproduction, a very long time ago. "Our capacity to relate and to care for one another" looks a lot like oxytocin, which therefore belongs to all of us who reproduce sexually. There is nothing stopping artificial intelligence from making us humans return to "relate and to care for one another." Hugging, talking, laughing, dancing. Trusting, being trustworthy. Sex, relationships.
You know, I think Yuval Harari hit the nail on the head when defining humans as those mammals capable of gathering in groups of more than just a few dozen, by being able to believe in abstractions — like "a country," "being a fan of a soccer team," a religion, etc. Harari mentions how difficult it would be to keep forty thousand chimpanzees well-behaved in a stadium, and yet we humans do that every single weekend.
Which abstractions will we believe in, with or without AI? I think this part isn't really under attack.
Nor is our capacity to relate to one another under attack.
So both our relating-animal side (oxytocin) and our human side (believing in shared abstractions) remain untouched. They aren't being replaced by anything.
What are AIs — much like what ChatGPT did with mathematics — actually replacing?
Something else. But neither our capacity to connect with one another nor our ability to gather in the thousands, millions, or billions around abstractions. Just my two cents.
Your assessment is depressing -- the thing that makes us special has gone from "thinking", "curiosity", "understanding the world" to "we don't kill each other when gathered in a stadium".
Heard from one mathematician recently - math is not about problem solving, but about the artifacts that are produced in the process. The new Navier-Stokes solution for singularity isn't worth a million, it supposed to generate new mathematical methodologies, tooling and lead to additional discoveries, like the graph theory.
I happen to be (re)reading Strogatz' book "Nonlinear Dynamics and Chaos" right now. It's beautiful thing, and nothing in the "age of AI" threatens to equal it or in any way diminish my enjoyment of it.
I think the point is that in the "age of AI" virtually nobody will have the opportunity to follow a career and produce works like Strogatz was able to do.
To me it seems the ultimate question is why would we expect humans to have an advantage at anything in the near future. A few years ago that would have sounded insane, but intellectually I don't doubt frontier models are superior to the average person. Even in the arts and humanities, give your preferred frontier model an interface and a way to "see" its work and it'll make the average person's work look like toddler scribbles. Humans still have some advantages, some places more than others, sure. Working with a designer recently I realized how bad, or maybe average, frontier models were at design. But I highly doubt the vast majority of people will be economically viable. Maybe this is one of the great filters, a society driving itself mad when freed from necessity of economic utility and without the big philosophical questions having answers.
Hacker News is so depressing these days. One doomer post per day to keep the valuations up.
Nothing has changed in math. Math is not solved nor has the human been kicked out of the loop. Same with programming.
*I said nothing really changed because LLMs becoming superhuman at deduction was priced in with o3 and neither the peer review, training nor publishing methods will get a revamp beyond what could already be done with SQLite and a website.
I'm no mathematician, but my impression as someone who at least does a lot of applied work with maths is that the main thing that's changed is that the yardstick by which academics earn recognition is being re-assessed.
But from my perspective proofs have never been the most interesting part of maths. What really interests me is the intuition that leads to new applications, and to new questions. Newton, for example, gets more credit for calculus than Leibniz because he's the one who demonstrated how darned useful it is. Erdos is arguably more famous for asking interesting questions than for answering them.
I still don't see LLMs seriously contributing to that facet of mathematics any time soon. Every so often I ask one to suggest a good binomial confidence interval for a particular application, and it still tends to just suggest one of the subpar options that everyone learns in a first year stats course.
I’m on your side on this overall, I think. And I suspect we’d agree more than disagree on nuances. But saying that ‘nothing has changed’ is very obviously wrong.
The doom posts will continue until profits are up.
Jokes aside, its like working for a company, individually you can lift mountains and someone else will take credit. When you use LLMs for a single bit, all credit goes to LLMs lol
This was the top comments when the submission disappeared from the front page.
Now the thread has been cleaned up and a pro-defeatism comment is the top comment and the submission is on the front page again (I'm not alleging moderator intervention, user mechanisms are sufficient).
the above, a "sorting" machine is the primary usage of hyperscalers currently, they're just trying to find new uses to boot for extra money/legitimation.
the browser industry
the phone industry
the CAs
JavaScript
it's all paid for by those wanting to sort humanity into whatever bucket the can fear monger the peasantry into for aweek or however long it takes the classification system to sort out.
gentrification works, but we chose forcible displacement now we have to live with the forever consequences.
would you give guns and bombs to the displaced native americans who taste blood over their beads and trinkets?
we've been inside the event horizon of the singularity for years, the tax bill will only get worse unless we recognize it for the tick that it is.
yeah nothing changed in math. mathematicians are weeping for some strange reason (maybe paid by OpenAI to weep?). And Terry Tao is posting blogs on AI + Mathematics because he was bored (or because he was also paid by OpenAI).
> One doomer post per day to keep the valuations up.
Yes, outsiders (investors, journalists) are given a false impression while insiders (software engineers) are supposed to give up. Double win for the agitprop machine.
It's probably because with the release of each model it is becoming more and more difficult to see how a person's livelihood and way of life continues. Uncertainty stacked on uncertainty.
How will it pan out, no one really knows. The leading frontier labs are continuing to hire aggressively. But who knows for how long or for long or near-term goals.
> Today, the mathematicians are weeping, because the machine smashed their tower first. But tomorrow, it may be the physicists, the economists, the illustrators, or the writers who weep over their fallen blocks.
Isn't it extraordinary that these models still can't write well? I mean, they write passably well, but they all have a highly characteristic style that you can spot from a mile away. These language models can crack the toughest open problems in math, but they haven't yet cracked human-like writing, especially long-form writing, without exposing themselves. This is very very odd, IMO.
> I am not one of those AI people who believes that hundreds of millions of jobs will be wiped clean from existence in the next five years
"Wiped clean" is the wrong phrasing, and 5 years is a short timeframe given the ability of some sectors of the economy to resist change. But yes, hundreds of millions of white collar professionals will need to rethink their careers and their business models within the foreseeable future.
Just today there was an HN article about how shady the dental industry is. In the future, you will go to a special dental imaging facility where a modestly-compensated technician images your whole mouth and feeds the results into an AI system, and when you get home you can look at the assessment and chat with the AI about it. Then you can potentially go visit a dentist, oral surgeon, etc, if you actually need work. This system will produce far better dental health outcomes at far lower cost: the diagnoses will be more accurate, and there will be no bias towards additional, unnecessary procedures.
> In the future, you will go to a special dental imaging facility where a modestly-compensated technician images your whole mouth and feeds the results into an AI system, and when you get home you can look at the assessment and chat with the AI about it. Then you can potentially go visit a dentist, oral surgeon, etc, if you actually need work. This system will produce far better dental health outcomes at far lower cost: the diagnoses will be more accurate, and there will be no bias towards additional, unnecessary procedures.
Right up until the sellers of dental supplies find a way to...
Indirectly influence model training to increase the frequency with which models recommend dental work and/or lower the bar for what they determine to be "necessary"...
or...
Directly influence model recommendations by paying model providers (who will be happy to take that money).
The point being that models (and particularly the humans that control them) are presumably just as corruptible as the humans they are replacing.
No one wants that. People pay other people to do things well. No one wants to need to discuss orthodontics with a bot, they would rather pay someone to know those things and think about them.
>Yes, some are crying about bruised egos, the feeling of wasted years, a creeping sense of status obliteration, the frustration of an unfair competitor, the indignation of feeling cheated and mistreated, and uncertainty about the future. But they are also mourning...
This nails it, however IMHO its almost all bruised egos and feeling of wasted time. I don't know the ratio of A:B but I also don't know anyone that is in the latter category of feeling doom and mourning that their craft is about to regress.
I don't know what's happening exactly, but I am genuinely astonished how little people seem to care about people losing something real, dismissing it as "bruised egos", using petty terms like "whining" and "crying", or calling them some insult for the crime of being angry or sad for having a big chunk of their life pulled out from under them. I'm referring to the big picture of common talking points, not just this case.
I guess I'm not astonished that people are so bad to each other in general, but more that in the case of genAI it's so prevalent in places that seemed more elevated previously.
Part of me wonders if this is actually a form of self-defense. The misery of others can provoke sympathy or the opposite: Angry pushback to protect oneself from dwelling on their misery.
The doom and mourning is that it's no longer their craft. Their involvement is on the threshold of no longer being useful. What does it mean for humans when the best their involvement accomplish is slowing down progress?
None of them have pointed to any of the solutions and said "this is real innovation" - because it's all been mining existing ideas and applying them elsewhere.
Imagine you spend years working on a solution to one of these problems. Only to realize after you publish that more than half your answer already existed in another branch of mathematics and you spent a bunch of time re-inventing it.
Yes the first big solve by OAI was "stolen" and that is tragic, and pretty bad. But it looks like this new batch, the one people are crying about, has none of that stink.
I think there is totally justified distress knowing your source of livelihood may be in danger.
That said, I don't think the reactions have been entirely circumspect.
1. Is the role of math academics really going to go away? Is there concrete evidence of this? Faculty still have very important roles to play, training students, training engineers, determining the direction of research. The breadth of math is absurdly, perhaps infinitely, wide, especially if including applied math.
2. You need to be a bit crazy to go into pure math academia in the first place. If you value the pursuit of knowledge for its own sake, shouldn't the emergence of such powerful tools to that end be a good thing?
I need to do some more research on this. Because I've always been told that AI, more specifically LLMs, are "glorified autocompletes". Yes they have huge data sets but ultimately they can only provide answers based on data that they were trained on.
So how can they possibly solve problems that humans have worked for decades or centuries on without being able to solve? How did they find something new? Is it that they were able to deduce the solution by examining all current data sets? Or simply brute force it until the produced solution passed all necessary tests?
The following certainly does not describe all mathematics or all LLM operations, but its my mental model for why LLMs are so effective in several fields.
Lots of mathematics entails recognizing that a tool/techniques that works in one area can be adapted to a completely different problem. For a human to do this requires having a robust mental model of the technique and the problem itself, and probably having just the "right" mental model to see how they fit together. And we are talking about extremely hard/sophisticated techniques and extremely hard/sophisticated problems, so the ability to deeply appreciate either can require years of study. And on top of that, even if the mathematician has sufficient understanding to develop the intuition that the technique might work, they will need profound fortitude, skill, and patience to see the solution through.
Unlike human mathematicians, who will develop a deep understanding of only a relative handful of techniques and problems in their lifetime, LLMs have ALL written techniques, problems, solutions, etc stored in their internal representations. So when they ably match a problem to a technique, we can imagine the operation as a supercharged autocomplete, or even an extremely proficient search engine. Their stroke of genius is really a consequence of capacity, moreso than cleverness.
They have access to a much larger corpus of information than any single human can manage in his one brain. No human mathematician reads all the papers and has perfect recall on them. The answers have always been there, but no individual has been able to make all the right connections to pull them together and formalize a new discovery or proof.
> Is it that they were able to deduce the solution by examining all current data sets? Or simply brute force it until the produced solution passed all necessary tests?
Yes, both of these + an infinite token/compute budget and SOTA+ models. It's not like some hobbyist out in the woods with a GPU running Qwen 27B can do this.
I'm convinced the people who do not see what Mathematicians see simply have not considered that their jobs are just as vulnerable. The day when OpenAI replaces their own AI researchers with GPT will be upon us, and the response from the Mathematicians will be "First time?"
Knowledge without understanding would be just getting "42" and not being able to ask any follow-ups.
But I don't think that's where we are at the moment. I believe the results, proofs and papers can be reviewed and understood, just like if a human peer had published another result.
I also think that the speed at which results can be now generated can't be followed by our collective speed to understand them, using the methods we are used to.
As we enter the next phase where AI publishes using mostly references of other AI results, this will compound exponentially until it would take any human decades to verify a single result by hand end to end.
I agree translating a phrase doesn't teach you a language, and I also believe translators are an essential tool that results extremely helpful when learning a new language.
So instead of throwing the towel, could we develop and adapt ways to improve and aid our understanding and verification processes?
As usual the author is ending on a completely unrealistic positive note: "humans may come to value more highly our capacity to relate and care for one another".
Does relating to someone pay my bills? People will use the informational tools to improve their social status and resource accumulation, there is no doubt about this.
“ What makes us special, it would seem, is this capacity to compound.”
Yeah so you’ll compound using the AI tools and get more done. Stop crying that your tilting at windmills is now being done more efficiently and find new windmills to tilt in new AI-assisted ways.
There was a time, not too far in memory, when the value of being human wasn't about our intellectual prowess[^1]. We were creative with the human worth thing: being there in the time of need, faith, nobility or being a well-dreaded, literally-bloody viking full of beads in your beard.
Yes, I fear we will stop being the top of the food chain[^2]. But by god weren't we getting bored? Maybe getting off our high horses and going into the weeds won't be such a bad thing.
[^1] And even today, if you go to parties and keep bouncing into people that have no trouble picking up intellectually stimulating topics, you are in a lucky minority.
[^2]: More about my fears, which are unhealthy and you don't have to read but I feel compelled to include citations: https://w.ouzu.im/aweb/unhinged
I think an under appreciated part of mathematics has been contributing clean and elegant work precisely so that others could use that as a foundation for further work and new insights. This dump from Open AI seems to be the opposite. Huge and messy, incomprehensible and taken seriously only because of Lean.
There is this assumption that AI will contribute to faster progress in math but given the garbage dump of proofs which we have to take on faith are robust I wonder if the opposite is true.
My reservation could only be dismissed if AI turns out to be able to contribute fundamental new insights and pose new problems. This takes us into an area where AI progress has been slow to say the least.
At least with AI, you can download the LaTeX, upload the paper to your favorite LLM, and have it explain the paper at whatever level of granularity you like. That wasn’t possible even two years ago.
I think people vastly underestimate the ability of human to respect human performance despite being inferior to machines. Think about chess players vs stockfish, marathon runners vs a car, etc.
I think the crux is much more prosaic, as buried in the article.
> I also don’t want to lose my job to a tangle of GPUs.
To put a GPTism, it’s not about the knowledge or status, it’s more about keeping their job and money.
And that can only be answered by policies, and imo by UBI. So votes if you can people, protest otherwise, discuss, debate, lobby with your friends, families acquitances.
Jobs and money are bottom of pyramid needs. If we answer those with UBI I guarantee you status and purpose are the next ones.
Chess players vs stockfish isn't a good comparison because chess fans only care about the performance of maybe the top-50 players.
People may gain and be satisfied among their own peer groups. All good and healthy if that peer group is your local badminton club or knitting circle - something where effort and skill have rewards and people can make objective, tangible progress. But groups not oriented around such activities could turn even more toxic.
I am not quite saying "if you can't beat 'em, join 'em", but I know more math now than in any point in my life because I want to understand how LLMs work.
I understand there are many types of math and the mathematicians don't all want to sit around and do KV cache and gradient descent things, but surely a percentage are as interested as I am and can contribute to this new emerging field? I would wager that Xl+1=Bl Xl+Cl ℱl (Al Xl) makes much more sense in their mind than mine.
This is the best attitude to have about the current state. Unless you have some dramatically different sensible solution (and you probably don't when it comes to technology, because it seems to spread for reasons that would eliminate other sensible solutions) that will catch on and take over and replace AI: it's going to continue to mature as long as it's mostly useful to everyone. And AI isn't even a new industry, it has been maturing for quite a while, which adds more weight to the argument that having an attitude that adapts to technology (unless you wish to go solo) is a 'better' fit.
The dramatic solution can never be: 'we should all just want to do it this way because it felt better to me'. That never seems to work, from what I've seen. So there is a lot of public discourse, arguing, to determine if 'doing things the old way' is perhaps more better. And if not, maybe we just shed a tear and move on (to look for a better fit).
As a mathematician, I will never understand how my colleagues had never foreseen this. Okay, maybe you can believe in a plateau but at least accept as a possibility that there won't be one. This applies to every other human endeavour.
I am also sad, but my sadness is, in a way, priced in.
It was really quick. I stumbled across a comment from KConrad on MathOverflow on how useless AI was for research. That comment was from 2024. When it disproved the unit distance conjecture in May, the solution involved a breath of knowledge of the literature that it made sense it took a computer to make the connection. It only took 5 months for it to advance to the point that it was better than humans at almost everything. Even if you expected it, the mind boggles at how fast it was.
Also, it's impossible to really know how you're going to react to something until it happens to you. When ChatGPT came out, I already thought "in the long run they're going to automate almost everything humans love to do". Despite having 4 years to brood about it, I did not really know what it would feel like until it happened to me directly.
Programmers, artists, anyone who used to create any form of documentation, translators, there are literally so many.
Either these mathematicians thought it would never come for their jobs, because all of these other jobs were simpler or they've been living under a rock.
Either way, I don't feel for them any more than I do for all of humanity.
When anyone can push a button on a machine and out comes a math result, it still doesn't become theirs or anyone else's until they can internalize it and make it part of their thinking.
"I can’t solve these things, but maybe you people in the future can stand on my shoulders."
Seeing AI being lauded for solving problems like this makes me feel... uncomfortable.
We are feeding all works of the giants that we have all stood on into a huge vat, in the hope to generate something meaningful.
If we can't understand the output, internalize it, or build from the time and experience that a human would have gained from solving the same problem, it feels like a dead end.
When all the problems have been "solved" by AI, what's next? If humans no longer struggle to solve the problems that the previous generation have left behind, how do we progress?
The author mixes "Science" and "Mathematics". Mathematics is not a science. There is nothing empirical about it. By mixing the two concepts, a reader might think that AI is on the verge of solving all of science. Until AI gets good at digging large circular holes in the in the ground, I think Experimental Physics is safe.
Maybe math is more like a science now, though? It's as if ancient astronomers saw the results from a modern telescope. "Why even look at the sky anymore," they might ask. "And we don't even own the telescope!"
Maybe the answer is to look into how Big Science works? There's still plenty of work to be done figuring out what to do with the outputs from these new math-observing instruments.
I had visions of large automated warehouses full of chemical and biological components hooked up to science machines to do everything from mixing, boiling and printing to spectrograph and robotic assembly. Smart computers and humans would pick the experiments to brute force with exact billing.
I remember the same doom cycle during my PhD when GPT 4 came out [1,2]. It seemed like everyone in NLP was freaking out except me. A few years later and new CS PhDs are still graduating and joining academia and industry. Much ado about nothing.
Considering I currently live in Ithaca and have a friend doing a Math PhD, so I've heard from him some of the discussions in the department. I think the biggest shock for people is that individuals spent significant portions of their time on some of the problems that OpenAI supposedly solved (I say supposedly because all of the proofs have yet to be independently vetted). I understand that it's a shock, but I'm confident that in time it will be no more of a blip than it was for NLP.
A blip for NLP? What bespoke NLP research is about anything other than LLMs these days? How many companies are handcrafting bespoke NLP models instead of sending a LLM request? Really confused here.
My friend, who is a math professor, told me that they weep because they are about to become just like us developers: prompt writers and AI output reviewers.
> My friend, who is a math professor, told me that they weep because they are about to become just like us developers: prompt writers and AI output reviewers.
If it was about understanding interesting proofs that some AI came up with, and extracting their essence, I don't think the situation would be so bad.
I see the much larger problem in the now existing career prospects of non-tenured researchers in mathematics. Everybody know how precarious the career prospects in academia and how precarious often the non-tenured positions in academia already are. With the new AI breakthroughs in math, these have in my opinion even worsened a lot.
I love that we have new ways to solve problems. And it's been hard to accept that my own unique intelligence—which I've spent decades cultivating—just isn't as important as it used to be. I am developing new ways of thinking to better adapt to an AI-enhanced world, but I'm not done with the mourning process. We're all finding our way through this.
I object to a few of the assertions made by maths folk in the article- 1st being that Google Translate taught us nothing about linguistics. If you use google translate you learn less about linguistics than if you had to experience learning the languages first hand, maybe, but you can learn form just that output if you are determined to, ad, more importantly, the folks who built it and are still building it are still learning a huge amount about linguistics.
What are the relationships between many languages that become apparent, including code as a language that were not obvious before llms? Translation is fairly solved. The study of how and why languages, not at all.
A hypothetical... suppose AI "solves" (for your preferred definition of "solve") your field and what you used to do becomes useless or near-useless. But you still enjoy doing it and you also get UBI that provides for comfortable lifestyle regardless of what you choose to do.
Questions:
(1) Do you still weep for what has transpired?
(2) Do you continue to do what you used to do (with optional AI assistance)?
For me: (1) no, (2) yes and I think the same would be true for most people. So I can't help but believe that most of the anguish about AI is far more about a direct economic hit to people's livelihoods than it is about the impact to their respective fields. Which is more than reasonable. But then why not frame the conversation that way instead of beating around the bush?
I’d be okay with UBI and hobby intellectual work for the rest of my life. But I’m not a mathematician. Many of them probably have more of their identities tied up with their cognitive abilities and social standing.
For many people, the answer to 1 is yes. You maybe happy with our future where we putter around aimlessly as consumers, but some people want to live in a world where they can at least try to do something that matters. Virtually every professional mathematician is motivated by personally making a permanent contribution to human knowledge, no matter how small.
Article refers to Hugo Duminil-Copin, who also did a podcast with Brady Haran [1] about this subject, for him it isn't case of bruised ego, or gatekeeping. He realized that the way things were done were going to change, and it made him emotional, he is not pessimistic or against AI.
One of the driving forces of math achievement is an internal award (yes, friggin business speak).
The vanity, fame, self-improvement, it's very selfish as everyone does.
Now the fame coming from proving things like Riemann Hypothesis is taken away.
Self-improvement? relying on AIs make you stupid. It will be lost.
Vanity? Who else don't know how to use AIs? It cannot fill your void.
Now also the most important thing is the communication.
There will be less communications amongst mathematicians at least in person. On paper? maybe but mostly via AIs.
I don't think it's the communication that's lost, it's the motivation. People love to collaborate, but they don't always want to waste time doing it.
It's the same reason you see 'no AI' repo labels: only by forcing some standard on the community can the 'old way of collaborating' continue to exist.
There will for sure be new ways of collaborating, and walled off gardens like you suggest, where communication stops and everyone just shares some final product.
But, in some cases the product must be understood (or demonstrated) before value can be derived, and so collaboration will still exist.
Desire, and the 'shape' of collaboration has changed greatly though. Why collaboration has changed, is a completely separate issue related to economy and how each of us spends our time.
OpenAI didn't have to mass publish these solutions. They did it to make themselves look good. They are ostensibly making a tool for people, to better humanity. Instead, they chose hubris and self-interest.
Letting mathemeticians use these tools to reach the same conclusions would have been far less destructive, and potentially, even exciting. Shame on OpenAI.
Mathematicians are smart enough to have figured out which way is up. You can debate the stuff outside someone's field not knowing the details but the insiders know what is happening. Ai may not be better than someone with very specific knowledge at this point but it is certainly better than the net. Once it gets optimized for every little super human knowledge, it can do better.
These guys know because they looked at it. Denying it is useless. But maybe some of these guys can figure something new using it and asking it to look for it.
I'm wondering if mathematicians are sort of going through what programmers have been going through recently, really questioning whether their craft can continue. But now it feels like, in the software world, at least from my seat, people can handle much larger scope and work on much more complex problems. If anything, my job has gotten a lot _more_ interesting.
So I wonder if mathematics will go through that too? A period of chaos and doubt, but finding new and more effective ways of working.
Mathematicians are grieving the birth of something that is, in a very real sense, the crowning achievement of mathematical ingenuity.
I never appreciated hard math much because my brain just can't get there. I thought so much of math was much ado about nothing, but now I see the art in math...not in the inscrutable formulas, but in the creation of AI.
Well done, mathematicians. You can now rest from your labors.
It's got to be alarming. Without a doubt, being not only on the frontier of yoyr profession, but in THE profession that is undoubtedly the most intellectually rigorous and well renowned and respected... It's got to feel pretty awful
We are seeing many fields being impacted. Makes me happy to see things like artcraft coming out that directly impacts the big tech companies themselves.
I think they might find comfort in knowing it's not just mathematicians - this is coming for all of us. Computers putting us out of work has been coming for a long long time.... and now it's here.
Mathematicians should web search the arguments when artists were hit by the wave. Scientists in general and people that think humans know better.
This is probably the first time in history deep thinking is being replaced by a machine, but the overall arguments are the same in all cases. Graphical artists saw it first, then programmers, now mathematicians.
No, there is not stopping the wave. No, society won't probably be able to support the same number of mathematicians as before. But yes, there will still exist mathematicians after the wave break, just probably completely different than the old way.
And yes, some people will still try to do artisanal mathematics and say it's better, it probably is, if the artisanal mathematician in question is doing deep creative and out of the distribution work.
Those of us who loved programming have already been through this.
I hate programming these days - back in the day, the cubicle-hell nature of "popular" frameworks was at least offset by being able to think through and solve interesting problems.
These days most of us are stuck in the "endless-review" loop with LLMs. You can't afford to not use it given the inflated expectations. As with all of modernity, productivity doesn't yield leisure - it just proportionally increases your workload.
Hardly surprising that the other side of the Curry-Howard correspondence is now getting hit with this. Math was one of those depts. where slow/deep-thinking was possible (CS was already insane 10 years back - now it's just absurd) - now even this fortress will be broken. Tragic.
My take is that it is an exciting time to be a mathematician since the frontier for interesting math problems is about to explode, and without prior art or references, it's green field for both AI and human. Think of all the new discoveries we'll make.
The beginning of this article is decent, the end sounds like a tobacco lobbyist touting the health benefits of nicotine.
> If intelligence becomes less uniquely human, we may come to value more highly what remains uniquely human: our capacity to relate and to care for one another.
Lol. How does the author think relations between people work? (At least those outside the family). Relationships require something that fills them with meaning - a reason why you would want to have that relationship in the first place. Without meaning, no relationship.
This is such an insidious propaganda targeted at the demoralization of entire professions.
Strogatz is an AI booster who "wept". Totally representative!
How much do they pay you? Does OpenAI have bulk subscriptions to your Substack?
> "Earlier this year, Shanmu Jin, a Chinese medical resident, used ChatGPT to solve a problem called Crouzeix’s conjecture, which professional mathematicians had failed to solve for decades."
I note that that these conjectures being solved by AI are named after people, minds knowledgeable and and brilliant enough to come up with the question in the first place and recognize its value. What we have in these AI math solving systems is the equivalent of the chess and go software that can beat humans: something that can adhere to a set of rigid rules to reach a win state once given a starting point. But, as Pablo Picasso said, “What good are computers? They can only give you answers.” These AIs are a magnificent achievement and will change mathematics and coding but can they ask earthshaking questions? Could an AI identify conjectures that mathematicians recognize as a worthy question that will lead to new insights? Where is HAL9000's theorem or the M5 Multitronic's conjecture? Maybe they can someday but I don't see any immediate prospects for it.
Please spare us the "AI will surely keep getting better forever" (unlikely and don't call me Shirley), "moving the goalposts" (I myself haven't set any), etc. non-arguments.
I still remain hopeful that this is a step change in capability and capacity that we can adopt and adapt towards our own purposes. What was taking decades for us to do has been reduced to days and dollars. So while we’re witnessing a forest fire consuming entire fields of open problems in math, the best upside would be finding new problems that come from learning how to work with the new tools.
This is what it seems like so far for software. The speed limit has changed. It’s interesting to explore what that means. Extending the analogy, long ago you could be a race car driver part time; that would be pretty laughable for an F1 driver. It’s a very specialized skill and the optimal athlete is quite different for driving a car than for running, for example. That feels like what I’m seeing in software.
The most effective folks are much faster and better with these tools than average. It’s a different skill set.
I think that formal verification makes Math much closer to code than many other fields. But I’m eager to see the first mathematicians that are dramatically more proficient with the new tools than average.
I mourn the loss of comfy, intellectual, thinking jobs like those of the mathematicians where people could spend time pondering without the immense pressure that would come from doing something like that in a corporate environment.
I wonder how much this is like a tremendous telescope being invented which can see new worlds with utter clarity. We could verify that a planet was habitable... but it wouldn't bring us any closer to visiting it.
This current moment we are in feels like something out of the Remembrance of Earth's Past trilogy, bit instead of humanity becoming super depressed and hopeless about a future alien invasion we are super depressed and hopeless about LLMs destroying all our hopes and dreams.
These guys are still in the early stages of grief. They should look at coders; we've already been there. Coders don't assume coding is going to remain a profession. Why should any other profession be exempt from disruption?
Honestly, there are much bigger fish to fry, like how will everyone pay their bills, and how will we prevent catastrophic AI.
...except it is exactly the opposite of your big brother destroying your tower. Instead, it is your big brother showing you this method using a tool to build many more towers at astonishing speed!
I get the sadness (and, as a software engineer, certainly feel a real existential threat myself) and feeling diminished, but at the end of the day that is all just ego and I very my agree with the end of the article - who cares who came up with it and on what shoulders we stand, as long as it is saving lives and improving our understanding of the universe!
I strongly feel most angst is because Mathematics has become yet another capital intensive game to play. Rather than a noble, purely intellectual practice.
> Think about a world where non-mathematicians leapfrog the field after a few AI prompts. It would be a world with more knowledge. But it might be a world with less understanding.
This seems like a good summary of the article, and I think the answer here is obvious.
So what?
News flash folks: we do not have the knowledge to survive on our own. If a solar flare deletes the electric grid, the first thing that happens is 8 billion people die in the next year.
We survive on abstractions others have built, and we have a global dependency web.
AI abstracting knowledge is neither new or dangerous; if it is dangerous, this certainly isnt the argument to prove it.
Not sure about that title, it did bait me into a click. "Mathematicians are now facing something similar to generational trauma of structural racism born of exploitation, slavery, and colonialism?" https://en.wikipedia.org/wiki/I_Know_Why_the_Caged_Bird_Sing...
But regardless, the detection of breast cancer via AI made me think of phlogiston https://en.wikipedia.org/wiki/Phlogiston_theory . "Phlogiston theory states that phlogisticated substances contain phlogiston and that they dephlogisticate when burned, releasing stored phlogiston, which is absorbed by the air. Growing plants then absorb this phlogiston, which is why air does not spontaneously combust and also why plant matter burns. This method of accounting for combustion was inverse to the oxygen theory by Antoine Lavoisier."
It could be phlogiston. AI is super smart theory states that AI is super smart and that is a single thing can do tasks very efficiently. But it's so smart, we can't understand it, so we humans can't help it, it'll take AI to make it even smarter. That's what's holding it back. But then it'll solve everything.
Or it could be oxygen. AI is super-fast-and-parallel theory states that AI is not a magical monolith but a bunch of pedestrian programs that run fast and in parallel, thanks to hardware (GPUs) that's good at that stuff. But since it's all going so fast and at the same time, something a single human cannot do, humans can't really see how it works. But if we could, we'd probably just see its just doing stuff programs did before. So what's holding it back is that you have to keep throwing hardware at it, and eventually you run into the limits of how fast you can build that hardware or power it.
It all might be stuff humans were better at, when approached one-on-one, but against a swarm it loses. You get a billion doctors together to look at a single mammogram, then tell them if it cancerous, then do that again a billion times with each doctor. Then ask those billion doctors on the billion-and-one mammogram to give a diagnosis. Heck, do that with a billion toddlers. I think either might be able to beat the AI. I don't have a billion doctors or a billion toddlers--frankly I don't know which would be more difficult to handle.
To know if it's oxygen or phlogiston takes probably a demonstration like this "Phlogiston remained the dominant theory until the 1770s when Antoine-Laurent de Lavoisier showed that combustion requires a gas that has mass (specifically, oxygen) and could be measured by means of weighing closed vessels." Maybe the data center financing trouble will be the demonstration that the mass in the gas is just VC-money hardware.
I know why you got a billion cages with a billion birds and a billion bird listeners to compare a billion songs to the few songs we like to hear, and then packaged all that into a single bird-looking thing to make singing-like sounds: So Altman can get that VC money.
Isn’t it deeply exciting that the proofs look so alien?
Isn’t that in itself the new frontier for human understanding?
I would have thought that mathematicians would have found alien forms of maths to be astonishingly compelling, must learn, must know, must understand.
Instead there seems to be a sort of shoulder shrugging lament “we don’t understand it”.
I would barely be able to sleep with excitement at the potential for where this could lead. Like finding an ancient tomb full of answers to our deepest questions along with the promise of more.
How deep does maths go? Is it “solved” or have we just been given tools to delve ever deeper?
Where is their curiosity - don’t the want to find the bottom?
>I wanted to talk to one of the mourners to understand their technological grief. I wanted to know if theirs was a familiar case of bruised ego or disappointment—akin to, say, a boy who spends an hour building a tower out of blocks and watches his big brother smash the thing to smithereens—or something stranger and more profound.
I'll be honest. The response to mathematicians, even this one, makes me concerned about the lack of empathy and honestly just theory of mind of many people in tech. It's not a mystery why people are upset that their field, for many the singular passion to which they've devoted their entire lives, is being annihilated so that a massive company can boost its IPO valuation. It's not "bruised ego" ffs.
‘Tech’ culture has been getting nastier, more vicious, and more zero-sum for years now. It wasn’t even all that long ago that I remember feeling hurt when a friend of mine sneered about “tech bros.”
But I get it now. I see a certain type of guy in an AWS fleece and instantly judge him, round him off to some kind of bully. Harsh, unsmiling, tweaking on stims, telling you to cry harder. Or maybe he’ll open up tell you his theory of how we need eugenic breeding facilities on the moon, or which countries we need to “glass.” It’s gotten so ugly.
I know this seems mean, too. Coming out of nowhere. Strawmanning or whatever you call it. Literally inventing a guy to get mad at. I’m aware of the irony. I don’t know. I guess it’s another kind of mourning, and I don’t know how to express it. I thought tech people were supposed to be like Woz.
The interesting answer is we don't know. Many of the math problems that make our computers efficient were developed hundreds of years ago with nothing we could do with them.
It is mostly impossible to figure out what we find when we solve these problems. But occasionally they'll lead to real world efficiency in algorithms we use and it changes the world.
I have little sympathy, since I think it is a result of many decades of complacency when it comes to thinking about why want to people do what they do and instead just enjoying being the ones with the results and money. People who love the process and see the human as inherently valuable won't have a problem. I'm more shocked that there are so many brilliant people who are so results-oriented and don't even have a concept of value outside of that. I'm kind of disgusted by the tears actually
> I have little sympathy, since I think it is a result of many decades of complacency when it comes to thinking about why want to people do what they do and instead just enjoying being the ones with the results and money.
It's not clear from your comment: Are you talking about math professors?
If so, what money? They make a living, but it's not that great. I just checked the salary of two associate professors at my university: $80-85K.
And keep in mind they often start their careers quite late. Often multiple postdocs after PhD. Starting a tenure track position in your mid 30's is not common.
> I'm more shocked that there are so many brilliant people who are so results-oriented and don't even have a concept of value outside of that. I'm kind of disgusted by the tears actually
The whole point of the article is that the person crying is because he loves the process and is worried the human connection will be gone.
This is exactly my perspective as well. Seeing humans as inherently valuable is the key. It's shocking to me that so many people seem to have been reducing humans to the results they are able to produce and now that the results appear to be drying up, their perception of their own human value is going down with it.
Of course the other Abundance guy joins in on the AI Inevitability Soothsaying.[1] It really is the perfect vector for the AI sirening. You just take the inevitability and awesomeness as a given. That’s the real point. But you write about the “grief” and the loss of “identity” and psychology—oh my the feelings. See, we are left-liberals and we care so much about people’s feelings. All the investor class and their hype is perfectly on track is about to fuck us the rest of us. But the feelings about people can’t “understand” and “discover” is what matters.
> gatekeepers bemoaning their gates being blasted off the hinges.
i think that's 85% of the response from software devs if not more. All of the devs I know who actually like to build have embraced AI and the new capabilities that come with it. The ones that guarded their little corner of code proclaiming only they, and their inner circle, have the power to comprehend it are the ones crying in the corner.
Getting those fields wiped just shows how unnecessary those fields where in the first place. I'm a programmer. I am the adapter between a stakeholder and a machine. I am just needed because the stakeholder lacks the knowledge to tell the machine what he wants. If he can use this new fancy adapter called Agentic AI now I happily quit my job and go on finding something that makes more sense in the first place.
The same goes for math.
Let's find some things that bring value other than just the price of a stock.
Broken take, with out this trail of mathematics that lead us here we'd have never reached this place. You think multi dimensional matrix math comes natively to humans?
At worst its time is past, but even that is unlikely.
I think beyond the specific elements of any domain AI eclipses humans in, overall, the notion of the thing that grants you status, prestige, and a living wage being commodified would spark in anyone a profound sense of dread.
Beyond just making you redundant in your job, the whole architecture of your existence, the thousands of hours of struggle, the sacrifice of putting off social games or personal enjoyment are now rendered moot in hindsight. You are made one step closer to complete worthlessness, which will surely continue as AI becomes a more satisfying personal companion, a more worthwhile friend, lover, etc.
How is one to feel safe in the progress of the future when the only hints of the wonderful post-scarcity utopia we can quantify so far is the removal of all human leverage via their labor? All it tells us is we will be bargaining with superintelligence with nothing to stand on, only a trust that the 5000 lab executives and researchers solved the most important research problem of all time on the first try.
And remember, these AI models were trained on your work, your culmination of effort and sacrifice, without any consent, credit, or compensation, then sold back to you for a subscription fee.
> You are made one step closer to complete worthlessness, which will surely continue as AI becomes a more satisfying personal companion, a more worthwhile friend, lover, etc.
I recently thought about this and fear that AI may further drive us humans apart.
Instead of working with humans, I increasingly work with a fleet of agents.
> the notion of the thing that grants you status, prestige, and a living wage being commodified would spark in anyone a profound sense of dread.
Not for those without status (which is most people on this planet). But yes, AI is set to wipe out most established hierarchies and their gatekeepers, and to equalize most fields. A profound sense of dread is something most ordinary people live with throughout life, and if AI can reduce systemic unfairness, I bet most people will actually find some degree of relief from that dread. The complacency of the formerly-statused being shocked along the way isn't much of an argument against that equalization.
> Beyond just making you redundant in your job, the whole architecture of your existence, the thousands of hours of struggle, the sacrifice of putting off social games or personal enjoyment are now rendered moot in hindsight.
This passage answers itself, doesn't it? You can sense those things you postponed fun for (work and the apparatus around its struggle) were never worth it. So why fight for us all to have to keep working just to live? Isn't a post-scarcity world the thing we should all be fighting for?
It's more or less reverse to the mean. The period in which a people had both access to education and leverage through their labor and intellect is super short. For most of recorded history, the bulk of humanity lived as peasants, serfs, or slaves. They were mostly illiterate, bound to the land or to a master, and had little power to bargain over the terms of their (or their children) lives.
Unfortunately, I think this is a human failing being exposed rather than anything else. We like to build conceptual models of how things work, but they are often tinged with should. Reality doesn't care how things should work. It only cares about how things do work. It's always jarring when the should turns out to be false.
Philosophers for millenia believed that human beings had meaning, purpose and set out to explore what that could be. It was a noble profession for a long time. Once we realized that there was no hidden spark, ergo no purpose, the study of and the prestige associated with philosophy took a nosedive. Yes it is still studied but it carries nowhere near the respect it once did. Mathematics seems to be suffering the same fate.
I think the fix is to get started on post scarcity economics now. Sooner or later we're going to have to come up with practices that boost or limit endeavors based on how people feel about them, rather than based on how much money somebody has.
It doesn't have to be ((post scarcity) economics), it can be (post (scarcity economics)). Both systems can coexist for a while, one providing a bit of a safety net while the other falls apart.
Counter point: AI is trained on output from humans. We all made AI, together. It belongs to all of us. We use it to benefit us, and we celebrate our wins together.
We'll be free of cancer, and dead on the inside.
You are made one step closer to complete worthlessness
Nobody's worth is tied to source code output.
The only thing constant in life is change.
It's mainly about status. No one cares that much about AI automating drug discovery or coding, but it's bad when it assists in math. Math results are attached to individuals , whereas for cancer drugs or other medical discoveries, it's more of a team effort by a lab. AI now has the effect of turning math into something that is more lab-like and less about the individual.
Yes, and I think over time there will be a blatant inequality in who is commoditized and who isn’t.
If AI engineers didn’t create the data to produce the models, and they increasingly don’t write the code to produce the models either, then why are they treated as the agents of change rather than the subjects of change, like mathematicians are?
When I was a kid I built my entire identity around being #1. I was the most talented kid in school, anything endangering that resulted in an instant identity crisis.
Then I went to college and I understood that there are people who, for one reason or another, are thinking in ways so advanced I'll never catch up. I'll never be the #1. I'm actually much closer to being average than I thought.
But this doesn't mean I should just give up, lie down in my bed and cry. Since then I've learned a lot of skills - most of them being crap at best, but that's not the point. What matters is my own subjective experience. The fact that despite objectively not being good, I see myself as a skilled person with rich life.
Once I was watching a YouTube video about elderly care and there was a phrase along "These people won't achieve anything more in their lives, my goal is to keep them occupied until they die" which is a bit morbid at first glance, but it actually makes so much sense as a life philosophy.
You know we (tech as an industry) have done this to a bunch of people already, right?
Thats what "disrupt" meant
I would answer to this that the mathematicians (humans) are the ones who give any meaning to mathematical discoveries. If we don't have mathematicians anymore, the result is that AI can find whatever they want, but 99% of that will be useless waste. Outside of practical applications, the only reason most mathematical results have any interest is that lots of mathematicians spend time trying to find their solution. Once humans stop caring, mathematics done in an automated fashion will also stop having any value, other than its possible use in finding solutions to existing engineering problems.
> bargaining with superintelligence
This part is nonsense, still. There's no known AI -> AGI path, and superintelligence doesn't mean anything, and AGI is assumed to be (going to be) both malicious and a slave, both for no good reason.
Nah. There is nothing beyond being made redundant in your job and labor leverage. That is all. It has got nothing to do with resentment over fucking machines. It’s all about people (the executives that you mention) fucking us over. The end. Completely human problem.
I know I’m being sold some bullshit when this is made into something inherently existential and psycho-identitarian. An egalitarian future of labor-worthlessness means that there is nothing above us to dictate anything at all—maybe not even nature itself, save for meteors and other cosmic events. I’m not afraid of being “worthless” in that world of complete freedom. Fuck no.
“Worthlessness”
Consider this… in the grand scheme of things, we are on a tiny planet in the universe. What cosmic contribution could you make?
Most people won’t make anything even close to “a ding in the universe”, as Steve Jobs has been reported to say.
So they may as well enjoy their life. And your worth can be to your family, to your children, your parents who took care of you.
Learning a hobby. Practicing religion. Mindfulness and meditation. Doing sports and improving your own body.
Look around if you are a heterosexual man, for instance: many women are far more attracted to men that perform in the moment, than men who labor quietly to create a product. The former enables untold hours of honing social skills and calibration, and humor and performance skills. The latter is of more durable value to society, yet relatively few women are genuinely sexually attracted to a man doing the deep work. (By the way, it is also true the other way: most men are not attracted to women for doing deep work or being a rocket scientist.)
Animals don’t do “deep work” and most animals are attracted for far “shallower” reasons. If everyone has a UBI and AI does the “deep work” then that frees up humans to be like animals in a zoo or in the wild… doing all the displays to attract mates, having babies etc. That’s not nothing — in fact it is 99.999% of everything that happened in history and 100% of what happened in prehistory.
You’re just ceding that 0.0001% which represents technological progress. The actual dread comes from the fact that you and all of humanity will be as completely powerless to change things as cats or any random animal species is powerless now. The difference is you will perhaps understand your powerlessness more than they do. But in the good scenario, you’ll be like animals in a zoo. We are constructing this zoo for ourselves now.
We will remain on this blue planet while the AIs will colonize the universe. In fact I wonder why aliens would ever come to Earth, when they’d just send their AIs or robots. Look at this: https://news.ycombinator.com/item?id=46200502
For me the most obvious conclusion is, use your maths skills and get into open source AI.
Make AI as cheap and accessible to as many people as possible and we will likely be much better off.
The more people empowered by the tech the less like you will be “redundant” in the way you describe. You will own the important tools only the techno oligarchy own today…
Would you feel the same if you were a part owner of OpenAI? I bet you’d feel excited about the money you’re about to make ?
> How is one to feel safe in the progress of the future when the only hints of the wonderful post-scarcity utopia we can quantify so far is the removal of all human leverage via their labor?
I'm sure the Telegraph operators, human calculators, mine workers and all sorts of people have asked themselves this question. It's obvious that it feels strange to suddenly be part of the cohort asking but I assure you it's not new. And the answer hasn't changed much since.
> the removal of all human leverage via their labor
I’m not convinced at all that SI will ever be able to produce the correct result with little input. The advancements in capability I’ve seen in models is that they understand my intention better, and follow industry best practices better, so their output is often acceptable. But I absolutely have to make my intentions known, as detailed as possible, or I will get the mediocre, standard solution that falls out of the weights.
I’ve been having trouble with models always steering towards certain solutions - they insert a queue here, a mutex there, a backoff over there. If I remove those, and let the model freely rebase the PR stack, then it will re-insert those mechanisms because it has been specifically trained to do exactly that. It’s essentially boilerplate, smoothly aligning my codebase to match their weights. Which is often good enough! They are training the models well. But individual problems require individual solutions.
My personal take on the human part in all this is: We get to decide, and the models obey. Our decisions are now super leveraged. So let’s make good decisions, and communicate them well. The layer of where decisions yield the most leverage, has been pushed upwards (I see it on the type and function signature level, others will see it even higher), but IMO it won’t be possible to push it up much further without losing truth to the decisions we need to make for a good product.
I can kind of relate but I feel like I am mourning something different: the loss of the desire to seek truth in tech, math etc.
Nothing is validated or tested anymore. It’s all about the shape or believability or even how loud it is.
They dropped 100+ papers no one read. I am sure mathematicians are reading them now but even this forum has concluded that these problems are solved, without reading or validating.
It’s like everyone forgot “don’t believe everything you read on the Internet.” And it makes for a very boring discussion when everyone is just spewing unvalidated claims, layering them with strong beliefs founded on similarly unvalidated claims. It’s dull, without substance and just pure noise.
> I feel like I am mourning something different: the loss of the desire to seek truth in tech, math etc.
This is what I've been feeling too. It feels increasingly like the professional world has become a tower of scams. It's not worth building technical skills or focusing on quality; your boss doesn't know or care what good work looks like, he/she just wants your work to look good enough to his/her boss, who knows even less about the actual work being performed. And everyone reports up to an MBA CEO who was brought in from a completely different industry.
I want to work in an industry where skill, diligence and expertise is rewarded and respected, but from what I'm seeing political ability is 95% of the game and caring too much about the work is a career liability.
+1 We need human verification.
Not sure I agree - they dropped hundreds of papers, most of which were so badly written that they were incomprehensible. If it wasn’t for the lean certificates on 30% of them, the mathematical community would have told them to go and whistle.
I think the consensus here is that most of the papers are effectively correct. But it would take years of study just to understand most of the problem statement - so we have to wait for the mathematical community to digest the borderline-nonsense that OpenAI spewed out.
This piece circles, without naming it, around the concept of “deontic scorekeeping” central to the work of Robert Brandom on semantics. The idea that our ability to create and sustain conceptual systems depends on the give and take of reasons within a social setting. Brandom has been front of mind for me lately because elements of his theory both explain why LLMs should work in principle, and where they are bound to be radically deficient. An LLM encodes the normative regularities of our linguistic/conceptual games into its weights, but it cannot be a real participant in our games because it is incapable of staking durable commitments or changing its dispositions over time.
Worth reading: Robert Brandom, “Making It Explicit: Reasoning, Representing, and Discursive Commitment”
> An LLM ... cannot be a real participant
The participant is not an LLM, the participant is a company. The company learns. It adapts. It has a trillion dollars of skin in the game.
> The idea that our ability to create and sustain conceptual systems depends on the give and take of reasons within a social setting.
I read this sentence 5 times and I still cannot parse it.
What a coincidence, I've also picked up inferentialism but never really got into it.
I'm interested in the reversal that Sellars proposes - it seems clear to me that "representation" is not prior to the space of reasons, despite how unintuitive it is.
> An LLM encodes the normative regularities of our linguistic/conceptual games into its weights, but it cannot be a real participant in our games because it is incapable of staking durable commitments or changing its dispositions over time.
I see no reason why this can't be the case in the future, even though I think inferentialist-based theories are generally strong. Can't you force LLM's (or whatever AI architecture will exist in a decade) to stake durable commitments itself, then? They're at least autonomous enough to run computers. I agree that that is a core part to true meaning & autonomy, but nobody just lets them yet. I don't think inferentialism is a consciousness-based argument, either, so that escape hatch isn't available. I also don't think this is a necessary condition to engage in the space of reasons (but maybe then I'm misunderstanding it, or retreating to a more Sellarsian understanding). Could you explain on this more?
Though again, I only have the book sitting on my desk, and I haven't cracked it open...
This sounds super interesting but 477 pages is a beast. Would you recommend anything about this subject thats a bit more approachable?
Ok what about memory systems though (basically LLM modifies its own RAG context) - that should allow commits and changing dispositions over time?
I think in future, each company will built its own universe of mathematics consisting of prized discoveries. Maybe one Mathematical Universe per Company in the multiverse of mathematics.
tbf naming something "deontic" is not helpful
I don't think that's true. Why is it that I see more people using "shaped" and "load bearing"?
I think for me is, that history is not kind to the people who are left behind.
For example, weavers were one of the most powerful professions (if thats a thing) in the middle ages. In england there are the wool churches(not entirely weavers....), in the low countries, the weavers guild fomented revolutions, and shaped the borders of countries.
But that came to a crashing halt over the space of 200 years. slowly at first, then all at once. the power loom, then cheap imports from india turned a cottage industry into dark satanic mills. Yes there are/were specialists that still hang on, but they are like football stars you can probably name all the people who make money, the rest are barely scraping by.
For us, in the programming world, we will not have a 200 year grace period. Yes, AI produces shit code, but thats not the point. its cheaper and there are vanishingly small places were "good" code matters anymore. AI could be used to help a large range of people, provide support, trusted advice.
However because of the people who are funding it, that will not be the case. it will be used to reduce wages. Just like offshoring, resulting in china being the worlds manufacturing hub, AI, and the current people funding it will aim to make the expensive worker redundant.
In short, I weep, because Altman, and the money behind him ans his ilk want me destitute. I have committed the crime of wanting to earn a wage, and thus I must be punished.
It's profit chasing as well as practical - it kneecaps the educated workers increasingly asking questions about the morality of business and technology. It takes away the income that affords them the space to push back, threatens high ed, critical thinking. The salivating over AI makes perfect sense in that context.
I think Thompson has no understanding of endeavors like pure math or the theoretical sciences. In the words of Einstein, "I want to know how God created this world. I am not interested in this or that phenomenon, in the spectrum of this or that element. I want to know his thoughts; the rest [is] just details."
I think mathematicians aren't bemoaning their lost sunk costs. They're now aware that they may never again have the joy of being the first to pull up the edge of the tarp of ignorance and see the raw truth beneath _for the first time_. Their voyages of discovery, which give life meaning, may never leave dry dock again.
It is strange, because in a sense, when you start learning math, you never explore, you are being taught. Now mathematicians were able to exercise curiosity. That is going to change. Back to the ranks of eternal learners if you will. The fun was in the research. Now I think it will leave the door open toward more Applied math. What can people do with all the discoveries. The curiosity will be there. I think it is better that way. It will also put a cap on abstractions that overlaps. In essence, AI is less likely to create new theories, coin new terminology, etc. But it is better suited to recognize emerging patterns. That will probably simplify mathematics. Unless the domain of abstraction is infinite and with each new abstraction comes its own results but I doubt it. Who knows though...
> they may never again have the joy of being the first to pull up the edge of the tarp of ignorance and see the raw truth beneath _for the first time_
Until we can demonstrate AI consciousness, “seeing the raw truth” will be a human activity. Even now, verifying and understanding these AI proofs is a massive endeavor. Coming up with an intuitive (to humans) distillation of the finding remains an open challenging demanding expertise.
That's such a nice way to put it! I recently stumbled into "The Last First- Winter K2"[1] and saw the same spirit along with a similar misguided effort to win without the will, nor capacity to do it — e.g. influencers taking a stab at K2 is like prompting your way to results.
1: https://en.wikipedia.org/wiki/The_Last_First:_Winter_K2
Why is not like changing to a different type of vessel for the voyage? Unless and until it is all AI in closed system, could direct machines where to look etc.
I'll say it again: AI is capable of answering the questions put to it but AI is not yet capable of knowing which questions are worth asking. Mathematicians have no cause to weep, they will be fine.
> The story of human discovery and the triumph of the human spirit will soon be excised from this discipline. The Dinitz-Garg-Goemans counterexample was the most egregious demonstration. It revealed that the process of prompting novel proofs will be as auraless as ordering doordash. Watch as magic and mystery evaporate. Watch as the sun sets on our heroic age. Is there not something evil in the act of blocking all future generations of mathematicians from the experience of discovery? Forget about accuracy or even attribution. Something fundamental to the experience of mathematics is being taken.
> You are a helpless onlooker. Before you a channel through which humans have accessed the ineffable and sacred for thousands of years is being sealed for eternity.
https://kirwinhampshire.substack.com/p/the-dark-night-of-mat...
> They're now aware that they may never again have the joy of being the first to pull up the edge of the tarp of ignorance...
Not "never again", it would be extremely difficult but science and math are also built on random, trial and error, and intuitions that could not arise from AI.
> “Google Translate is amazing, but it has taught us essentially nothing about linguistics,” Strogatz said. “We don’t understand why it works. It just works. That’s the Twilight Zone. It is knowledge without understanding.”
This is not true, and it is the crux of an enormous debate we're now having across many, many fields.
Classical Chomskyan syntax (which models sentences as parse trees) has been enormously, astonishingly predictive of the rich structure in real-world human language. But we are quick to forget that we invented concepts like "words" and "noun phrases" specifically to help us analyze and predict things about human language. What LLMs and modern MT shows, definitively, is that there is another, totally separate way to describe these phenomena, which is both vastly less descriptive, and also vastly more predictive.
That these appear to trade-off is unfortunate, but it is NOT the case that we "don't understand why it works." We absolutely understand why it works, if we didn't understand we would not be able to improve these systems. What we do not have is a clean, descriptive theory that boils this down to something that is formally specifiable and analyzable. But those are different things, and this is the root of the disconnect between many communities working in and around these spaces (linguists vs computational linguists; mathematicians vs computational mathematicians; mech interp people vs empiricists).
"We absolutely understand why it works, if we didn't understand we would not be able to improve these systems" - Understanding how to improve something does not require understanding how it works.
Growing a plant does not imply understanding soil minerals or photosynthesis. Training a dog does not imply understanding it's brain. Using LLMs to improve a codebase does not imply understanding C++. Improving a PC with new parts, does not imply understanding RAM.
You can understand abstractions about the system, without understanding the system. Without gradient descent or other forms of automatic optimisation, do you think humans could build something as capable as GPT-1?
I think they're referring to the fact that neural networks are more or less black boxes. Their internals are blurry and not explainable in the same way that traditional linguistics tries to explain things - with rules.
Of course, ultimately that's because language itself doesn't follow simple rules like linguists would prefer. They're more like guidelines.
I still think mathematicians are going to be as important as ever. The LLMs are only finding what was technically possible given our current breadth of knowledge after brute force solving problems. Eventually it will run out of things that it can do with its training and the only way to get it to do more will be training it on new human found knowledge.
Finding that new knowledge may be exponentially more difficult, but it will be much more valuable.
> Eventually it will run out of things that it can do with its training and the only way to get it to do more will be training it on new human found knowledge.
How do you know this?
I liked reading an essay by mathematician Nestor Guillen that develops thoughts along these lines - the "convex hull of ideas".
https://birdsnfrogs.github.io/2026/09/12/Felix_qui_potuit_re...
Came here to say this. What AI is doing with math is essentially fuzzing, but looking for valid inputs that solve a problem and the inputs are mathematical abstractions. It's a cool approach, but AI doesn't understand what's going on, and without understanding it won't be able to create the next generation of mathematical abstractions needed for the next generation of proofs.
this is assuming that humans can be original in ways llms won't be, which I doubt will hold true
aren't mathematicians needed to create the problems? Everything solved so far is a question posed by a human. Which is probably why cracking diseases is more difficult (apart from man made viruses :/)
As a software engineer it is hard for me to feel sorry for these mathematicians. Software engineers are getting laid off because of advancements made by AI. Math researchers are employed at universities, and universities aren't laying off mathematicians now that OpenAI has solved some of their puzzles. Mathematicians can still feed their families, software engineers displaced by AI can't. Yet I see far more of these blogs about the plight of mathematicians, not enough about the plight of software engineers.
When software engineers spent the last 50 years eliminating the work of clerical, secretarial, and dozens of other back-office functions, were they concerned about how those people would feed their families? Do you think anybody but other software engineers feels any sorrow for them today, now that they are facing the same fate?
There are orders of magnitude fewer mathematicians with full time academic positions than there are software engineers. The economics are different and consequently academia tends to be more slow moving in reacting to market trends. It doesn't mean it isn't coming, but it will look somewhat different
I don't personally grieve for the likes of Strogatz or Tao, it seems likely both of them will be fine however this pans out. But many more mathematicians have been toiling away in precarity and obscurity and without tenure for years and years. And of course many mathematicians went into private sector roles as software engineers, actuaries, analysts, ML engineers and similar, and have been displaced there, too.
And highly visible blog posts written by famous mathematicians with large audiences and closely aligned with the news and hype cycles getting frontpaged on HN doesn't mean that mathematicians are disproportionately whiney, nor that software engineers aren't also writing about their plight or ending up on the front page as well.
To me this goes in the same direction as people not feeling sorry for software developers because our job is supposedly automating the job of other people (which I don't think describes the profession accurately as a whole at all).
Neither sits right with me. Can't we just all collectively acknowledge that we have to grapple with this new piece of technology that either is already or at least seems to be going to be hurtful to a lot of individuals?
Instead of looking at the in comparison limited group of people currently pushing this technology and asking ourselves whether we should be on board with their doing, we look to one another and are happy that someone else is now suffering just the same as we are. What a sad state of affairs.
As a software engineer? The career whose very reason, largely, for existing in this market is to automate jobs, with few notable exceptions? That one is somehow deserving of sympathy and that of mathematicians is not? Come off it. The notion is undignified.
> Software engineers are getting laid off because of advancements made by AI.
The bean counters laying off software engineers ought to take notes from the frontier labs' own hiring practices. They're still hiring lots of humans for business and engineering roles even when they would be better positioned than anyone to automate away those jobs with their world-class models (https://openai.com/careers/search/).
This is a silly analogy, and you're comparing very different entities.
Say you have a friend who likes making music (not professionally - just a hobby).
If an invention came out tomorrow that took the joy completely out of making music, would you respond with "It's hard for me to feel sorry about you."
Just because things suck for you doesn't mean it can't suck for others (in different ways).
It's not about universities, it's about grant funding over the next few years. It is very apt to collapse if AI is more useful than people. Why pay people to find this when tokens will do instead.
Why is it hard ? It's basic empathy.
What does your being software engineer has anything to do with feeling sorry for Mathematicians' job ?
It's a classic "I have it worse than them...everyone should feel sorry for ME and not them".
It’s only been a few months since LLMs started solving significant open problems in math. I wouldn’t jump to the conclusion that they have it better than software engineers.
In many ways it will likely be the opposite. Tech firms still need engineers to talk to customers and run experiments. What will the mathematicians be needed for?
Software engineers are getting laid off because of the end of zero interest rates, wars started by Putin and Trump, and a bit because of pandemic over hiring. The part that is due to AI is less hiring of juniors. Know your enemy before starting a fight.
What's your source for "Software engineers are getting laid off because of advancements made by AI". I haven't experienced that in my field and can't find any data to support that notion.
> Software engineers are getting laid off because of advancements made by AI.
This is said by a lot of CEOs trying to make layoffs look good, but I haven’t seen anything that suggests that it’s true.
> Yet I see far more of these blogs about the plight of mathematicians, not enough about the plight of software engineers.
Really?!? We’ve been living through 3 years of blog posts, LinkedIn hot takes, and podcasts talking about the plight of software engineers in the era of AI. There isn’t a week that goes by without an HN post about it.
I can feel empathy for the practitioners in a field that may have been profoundly changed, the same way I can feel empathy toward software engineers who are struggling with the changes in their own field.
In the end, we’re all trying to figure out where this leads. And how this will affect our lives and our work.
Unless this is satire, have you not considered how many proles have been laid off because they were replaced by technology or told that a spreadsheet model had decided their job was superfluous? Capitalism has been using technology to fond new ways to enrich itself for the whole age of personal computing, and arguably long before. Those Andreesen Horowitz comments about 'software eating the world' may have been exciting to people working at startups, but came off as rather sinister to people who were in the world outside softwareand just wanted to build a modest but comfortable life rather than develop unicorns and cash out.
The difference is it takes great intelligence to be a mathematician, whereas anyone can be trained to write code. It’s like the difference between an automotive engineer and a mechanic. I would argue writing code takes less skill than carpentry.
Software engineers still can feed their families. The notion that software engineers can not feed families is not consistent with reality.
Oxytocin is one of the oldest molecules in the world — it created sexual reproduction, a very long time ago. "Our capacity to relate and to care for one another" looks a lot like oxytocin, which therefore belongs to all of us who reproduce sexually. There is nothing stopping artificial intelligence from making us humans return to "relate and to care for one another." Hugging, talking, laughing, dancing. Trusting, being trustworthy. Sex, relationships.
You know, I think Yuval Harari hit the nail on the head when defining humans as those mammals capable of gathering in groups of more than just a few dozen, by being able to believe in abstractions — like "a country," "being a fan of a soccer team," a religion, etc. Harari mentions how difficult it would be to keep forty thousand chimpanzees well-behaved in a stadium, and yet we humans do that every single weekend.
Which abstractions will we believe in, with or without AI? I think this part isn't really under attack. Nor is our capacity to relate to one another under attack.
So both our relating-animal side (oxytocin) and our human side (believing in shared abstractions) remain untouched. They aren't being replaced by anything.
What are AIs — much like what ChatGPT did with mathematics — actually replacing?
Something else. But neither our capacity to connect with one another nor our ability to gather in the thousands, millions, or billions around abstractions. Just my two cents.
Great article!
(My thoughts on similar topics: https://blog.vladi.dev/en/articles/mudando-o-ponto-de-equili...)
Your assessment is depressing -- the thing that makes us special has gone from "thinking", "curiosity", "understanding the world" to "we don't kill each other when gathered in a stadium".
Heard from one mathematician recently - math is not about problem solving, but about the artifacts that are produced in the process. The new Navier-Stokes solution for singularity isn't worth a million, it supposed to generate new mathematical methodologies, tooling and lead to additional discoveries, like the graph theory.
I happen to be (re)reading Strogatz' book "Nonlinear Dynamics and Chaos" right now. It's beautiful thing, and nothing in the "age of AI" threatens to equal it or in any way diminish my enjoyment of it.
I think the point is that in the "age of AI" virtually nobody will have the opportunity to follow a career and produce works like Strogatz was able to do.
To me it seems the ultimate question is why would we expect humans to have an advantage at anything in the near future. A few years ago that would have sounded insane, but intellectually I don't doubt frontier models are superior to the average person. Even in the arts and humanities, give your preferred frontier model an interface and a way to "see" its work and it'll make the average person's work look like toddler scribbles. Humans still have some advantages, some places more than others, sure. Working with a designer recently I realized how bad, or maybe average, frontier models were at design. But I highly doubt the vast majority of people will be economically viable. Maybe this is one of the great filters, a society driving itself mad when freed from necessity of economic utility and without the big philosophical questions having answers.
Hacker News is so depressing these days. One doomer post per day to keep the valuations up.
Nothing has changed in math. Math is not solved nor has the human been kicked out of the loop. Same with programming.
*I said nothing really changed because LLMs becoming superhuman at deduction was priced in with o3 and neither the peer review, training nor publishing methods will get a revamp beyond what could already be done with SQLite and a website.
I'm no mathematician, but my impression as someone who at least does a lot of applied work with maths is that the main thing that's changed is that the yardstick by which academics earn recognition is being re-assessed.
But from my perspective proofs have never been the most interesting part of maths. What really interests me is the intuition that leads to new applications, and to new questions. Newton, for example, gets more credit for calculus than Leibniz because he's the one who demonstrated how darned useful it is. Erdos is arguably more famous for asking interesting questions than for answering them.
I still don't see LLMs seriously contributing to that facet of mathematics any time soon. Every so often I ask one to suggest a good binomial confidence interval for a particular application, and it still tends to just suggest one of the subpar options that everyone learns in a first year stats course.
I’m on your side on this overall, I think. And I suspect we’d agree more than disagree on nuances. But saying that ‘nothing has changed’ is very obviously wrong.
Go apply for some jobs. You’ll quickly come to the realization that something has changed.
And this is only the beginning.
The fear is the sales pitch. AI has some uses but nowhere near enough to justify the price tag, so we need something more to sell it.
Re depression: Seems like it is not just HN... You say nothing changed. Maybe that's even true.
But many people perceive this very differently, see link below. And perception is reality after all.
https://news.ycombinator.com/item?id=50093180
The doom posts will continue until profits are up.
Jokes aside, its like working for a company, individually you can lift mountains and someone else will take credit. When you use LLMs for a single bit, all credit goes to LLMs lol
> Math is not solved nor has the human been kicked out of the loop. Same with programming.
Is it like Chess and Go? There are still plenty of people playing for fun, but the machines are better at it than we are.
This was the top comments when the submission disappeared from the front page.
Now the thread has been cleaned up and a pro-defeatism comment is the top comment and the submission is on the front page again (I'm not alleging moderator intervention, user mechanisms are sufficient).
I'm sorry, but "nothing has changed in math" is a truly ridiculous statement.
Sure, there are people who overstate things. But that isn't an excuse to keep your head in the sand.
> One doomer post per day to keep the valuations up.
Wow that's very well worded.
my doomerism isn't about keeping valuations up, it's about tearing it down.
https://en.wikipedia.org/wiki/IBM_and_World_War_II
the above, a "sorting" machine is the primary usage of hyperscalers currently, they're just trying to find new uses to boot for extra money/legitimation.
the browser industry the phone industry the CAs JavaScript
it's all paid for by those wanting to sort humanity into whatever bucket the can fear monger the peasantry into for aweek or however long it takes the classification system to sort out.
gentrification works, but we chose forcible displacement now we have to live with the forever consequences.
would you give guns and bombs to the displaced native americans who taste blood over their beads and trinkets?
we've been inside the event horizon of the singularity for years, the tax bill will only get worse unless we recognize it for the tick that it is.
yeah nothing changed in math. mathematicians are weeping for some strange reason (maybe paid by OpenAI to weep?). And Terry Tao is posting blogs on AI + Mathematics because he was bored (or because he was also paid by OpenAI).
> One doomer post per day to keep the valuations up.
Yes, outsiders (investors, journalists) are given a false impression while insiders (software engineers) are supposed to give up. Double win for the agitprop machine.
It's probably because with the release of each model it is becoming more and more difficult to see how a person's livelihood and way of life continues. Uncertainty stacked on uncertainty.
How will it pan out, no one really knows. The leading frontier labs are continuing to hire aggressively. But who knows for how long or for long or near-term goals.
Even if this was overly long and mostly things I've seen before, I'm just very thankful that it wasn't yet another claude piece.
There was an interesting passage in the article:
> Today, the mathematicians are weeping, because the machine smashed their tower first. But tomorrow, it may be the physicists, the economists, the illustrators, or the writers who weep over their fallen blocks.
Isn't it extraordinary that these models still can't write well? I mean, they write passably well, but they all have a highly characteristic style that you can spot from a mile away. These language models can crack the toughest open problems in math, but they haven't yet cracked human-like writing, especially long-form writing, without exposing themselves. This is very very odd, IMO.
> I am not one of those AI people who believes that hundreds of millions of jobs will be wiped clean from existence in the next five years
"Wiped clean" is the wrong phrasing, and 5 years is a short timeframe given the ability of some sectors of the economy to resist change. But yes, hundreds of millions of white collar professionals will need to rethink their careers and their business models within the foreseeable future.
Just today there was an HN article about how shady the dental industry is. In the future, you will go to a special dental imaging facility where a modestly-compensated technician images your whole mouth and feeds the results into an AI system, and when you get home you can look at the assessment and chat with the AI about it. Then you can potentially go visit a dentist, oral surgeon, etc, if you actually need work. This system will produce far better dental health outcomes at far lower cost: the diagnoses will be more accurate, and there will be no bias towards additional, unnecessary procedures.
> In the future, you will go to a special dental imaging facility where a modestly-compensated technician images your whole mouth and feeds the results into an AI system, and when you get home you can look at the assessment and chat with the AI about it. Then you can potentially go visit a dentist, oral surgeon, etc, if you actually need work. This system will produce far better dental health outcomes at far lower cost: the diagnoses will be more accurate, and there will be no bias towards additional, unnecessary procedures.
Right up until the sellers of dental supplies find a way to...
Indirectly influence model training to increase the frequency with which models recommend dental work and/or lower the bar for what they determine to be "necessary"...
or...
Directly influence model recommendations by paying model providers (who will be happy to take that money).
The point being that models (and particularly the humans that control them) are presumably just as corruptible as the humans they are replacing.
No one wants that. People pay other people to do things well. No one wants to need to discuss orthodontics with a bot, they would rather pay someone to know those things and think about them.
I guess I'm lucky that I've always hated my job, because that prevented me from tying my self-worth to it.
>Yes, some are crying about bruised egos, the feeling of wasted years, a creeping sense of status obliteration, the frustration of an unfair competitor, the indignation of feeling cheated and mistreated, and uncertainty about the future. But they are also mourning...
This nails it, however IMHO its almost all bruised egos and feeling of wasted time. I don't know the ratio of A:B but I also don't know anyone that is in the latter category of feeling doom and mourning that their craft is about to regress.
I don't know what's happening exactly, but I am genuinely astonished how little people seem to care about people losing something real, dismissing it as "bruised egos", using petty terms like "whining" and "crying", or calling them some insult for the crime of being angry or sad for having a big chunk of their life pulled out from under them. I'm referring to the big picture of common talking points, not just this case.
I guess I'm not astonished that people are so bad to each other in general, but more that in the case of genAI it's so prevalent in places that seemed more elevated previously.
Part of me wonders if this is actually a form of self-defense. The misery of others can provoke sympathy or the opposite: Angry pushback to protect oneself from dwelling on their misery.
The doom and mourning is that it's no longer their craft. Their involvement is on the threshold of no longer being useful. What does it mean for humans when the best their involvement accomplish is slowing down progress?
It's the abject lack of shame that gets to me.
None of them have pointed to any of the solutions and said "this is real innovation" - because it's all been mining existing ideas and applying them elsewhere.
Imagine you spend years working on a solution to one of these problems. Only to realize after you publish that more than half your answer already existed in another branch of mathematics and you spent a bunch of time re-inventing it.
Yes the first big solve by OAI was "stolen" and that is tragic, and pretty bad. But it looks like this new batch, the one people are crying about, has none of that stink.
I think there is totally justified distress knowing your source of livelihood may be in danger.
That said, I don't think the reactions have been entirely circumspect.
1. Is the role of math academics really going to go away? Is there concrete evidence of this? Faculty still have very important roles to play, training students, training engineers, determining the direction of research. The breadth of math is absurdly, perhaps infinitely, wide, especially if including applied math.
2. You need to be a bit crazy to go into pure math academia in the first place. If you value the pursuit of knowledge for its own sake, shouldn't the emergence of such powerful tools to that end be a good thing?
I need to do some more research on this. Because I've always been told that AI, more specifically LLMs, are "glorified autocompletes". Yes they have huge data sets but ultimately they can only provide answers based on data that they were trained on.
So how can they possibly solve problems that humans have worked for decades or centuries on without being able to solve? How did they find something new? Is it that they were able to deduce the solution by examining all current data sets? Or simply brute force it until the produced solution passed all necessary tests?
The following certainly does not describe all mathematics or all LLM operations, but its my mental model for why LLMs are so effective in several fields.
Lots of mathematics entails recognizing that a tool/techniques that works in one area can be adapted to a completely different problem. For a human to do this requires having a robust mental model of the technique and the problem itself, and probably having just the "right" mental model to see how they fit together. And we are talking about extremely hard/sophisticated techniques and extremely hard/sophisticated problems, so the ability to deeply appreciate either can require years of study. And on top of that, even if the mathematician has sufficient understanding to develop the intuition that the technique might work, they will need profound fortitude, skill, and patience to see the solution through.
Unlike human mathematicians, who will develop a deep understanding of only a relative handful of techniques and problems in their lifetime, LLMs have ALL written techniques, problems, solutions, etc stored in their internal representations. So when they ably match a problem to a technique, we can imagine the operation as a supercharged autocomplete, or even an extremely proficient search engine. Their stroke of genius is really a consequence of capacity, moreso than cleverness.
Because the "glorified autocomplete" crowd likes to ignore the technical detail of how the autocomplete actually works.
They have access to a much larger corpus of information than any single human can manage in his one brain. No human mathematician reads all the papers and has perfect recall on them. The answers have always been there, but no individual has been able to make all the right connections to pull them together and formalize a new discovery or proof.
> Is it that they were able to deduce the solution by examining all current data sets? Or simply brute force it until the produced solution passed all necessary tests?
Yes, both of these + an infinite token/compute budget and SOTA+ models. It's not like some hobbyist out in the woods with a GPU running Qwen 27B can do this.
I'm convinced the people who do not see what Mathematicians see simply have not considered that their jobs are just as vulnerable. The day when OpenAI replaces their own AI researchers with GPT will be upon us, and the response from the Mathematicians will be "First time?"
Knowledge without understanding would be just getting "42" and not being able to ask any follow-ups.
But I don't think that's where we are at the moment. I believe the results, proofs and papers can be reviewed and understood, just like if a human peer had published another result.
I also think that the speed at which results can be now generated can't be followed by our collective speed to understand them, using the methods we are used to. As we enter the next phase where AI publishes using mostly references of other AI results, this will compound exponentially until it would take any human decades to verify a single result by hand end to end.
I agree translating a phrase doesn't teach you a language, and I also believe translators are an essential tool that results extremely helpful when learning a new language.
So instead of throwing the towel, could we develop and adapt ways to improve and aid our understanding and verification processes?
As usual the author is ending on a completely unrealistic positive note: "humans may come to value more highly our capacity to relate and care for one another".
Does relating to someone pay my bills? People will use the informational tools to improve their social status and resource accumulation, there is no doubt about this.
If you work in a nursing home it can pay your bills. Is it so far fetched that that kind of work might see a much needed status lift post-ASI?
“ What makes us special, it would seem, is this capacity to compound.”
Yeah so you’ll compound using the AI tools and get more done. Stop crying that your tilting at windmills is now being done more efficiently and find new windmills to tilt in new AI-assisted ways.
There was a time, not too far in memory, when the value of being human wasn't about our intellectual prowess[^1]. We were creative with the human worth thing: being there in the time of need, faith, nobility or being a well-dreaded, literally-bloody viking full of beads in your beard.
Yes, I fear we will stop being the top of the food chain[^2]. But by god weren't we getting bored? Maybe getting off our high horses and going into the weeds won't be such a bad thing.
[^1] And even today, if you go to parties and keep bouncing into people that have no trouble picking up intellectually stimulating topics, you are in a lucky minority.
[^2]: More about my fears, which are unhealthy and you don't have to read but I feel compelled to include citations: https://w.ouzu.im/aweb/unhinged
I think an under appreciated part of mathematics has been contributing clean and elegant work precisely so that others could use that as a foundation for further work and new insights. This dump from Open AI seems to be the opposite. Huge and messy, incomprehensible and taken seriously only because of Lean.
There is this assumption that AI will contribute to faster progress in math but given the garbage dump of proofs which we have to take on faith are robust I wonder if the opposite is true.
My reservation could only be dismissed if AI turns out to be able to contribute fundamental new insights and pose new problems. This takes us into an area where AI progress has been slow to say the least.
The dump from OpenAI seems to be the opposite: huge, messy, and incomprehensible, and taken seriously only because of Lean.
Math papers were hard to comprehend well before AI. This is hardly new. For example, here’s a screenshot of a paper from 40 years ago:
https://i.imgur.com/kPFlczp.png
At least with AI, you can download the LaTeX, upload the paper to your favorite LLM, and have it explain the paper at whatever level of granularity you like. That wasn’t possible even two years ago.
I think people vastly underestimate the ability of human to respect human performance despite being inferior to machines. Think about chess players vs stockfish, marathon runners vs a car, etc.
I think the crux is much more prosaic, as buried in the article. > I also don’t want to lose my job to a tangle of GPUs.
To put a GPTism, it’s not about the knowledge or status, it’s more about keeping their job and money.
And that can only be answered by policies, and imo by UBI. So votes if you can people, protest otherwise, discuss, debate, lobby with your friends, families acquitances.
Jobs and money are bottom of pyramid needs. If we answer those with UBI I guarantee you status and purpose are the next ones.
Chess players vs stockfish isn't a good comparison because chess fans only care about the performance of maybe the top-50 players.
People may gain and be satisfied among their own peer groups. All good and healthy if that peer group is your local badminton club or knitting circle - something where effort and skill have rewards and people can make objective, tangible progress. But groups not oriented around such activities could turn even more toxic.
I am not quite saying "if you can't beat 'em, join 'em", but I know more math now than in any point in my life because I want to understand how LLMs work.
I understand there are many types of math and the mathematicians don't all want to sit around and do KV cache and gradient descent things, but surely a percentage are as interested as I am and can contribute to this new emerging field? I would wager that Xl+1=Bl Xl+Cl ℱl (Al Xl) makes much more sense in their mind than mine.
This is the best attitude to have about the current state. Unless you have some dramatically different sensible solution (and you probably don't when it comes to technology, because it seems to spread for reasons that would eliminate other sensible solutions) that will catch on and take over and replace AI: it's going to continue to mature as long as it's mostly useful to everyone. And AI isn't even a new industry, it has been maturing for quite a while, which adds more weight to the argument that having an attitude that adapts to technology (unless you wish to go solo) is a 'better' fit.
The dramatic solution can never be: 'we should all just want to do it this way because it felt better to me'. That never seems to work, from what I've seen. So there is a lot of public discourse, arguing, to determine if 'doing things the old way' is perhaps more better. And if not, maybe we just shed a tear and move on (to look for a better fit).
> I know more math now than in any point in my life because I want to understand how LLMs work
The implication here is that you wasted your time learning that math, and the fact you learned that will not actually help you contribute to anything.
Now maybe you are closer to understanding the feelings expressed in the article?
As a mathematician, I will never understand how my colleagues had never foreseen this. Okay, maybe you can believe in a plateau but at least accept as a possibility that there won't be one. This applies to every other human endeavour.
I am also sad, but my sadness is, in a way, priced in.
I saw it coming since reading Kurzweil in high school and it's still heavy.
I just had a chance to flinch first.
It was really quick. I stumbled across a comment from KConrad on MathOverflow on how useless AI was for research. That comment was from 2024. When it disproved the unit distance conjecture in May, the solution involved a breath of knowledge of the literature that it made sense it took a computer to make the connection. It only took 5 months for it to advance to the point that it was better than humans at almost everything. Even if you expected it, the mind boggles at how fast it was.
Also, it's impossible to really know how you're going to react to something until it happens to you. When ChatGPT came out, I already thought "in the long run they're going to automate almost everything humans love to do". Despite having 4 years to brood about it, I did not really know what it would feel like until it happened to me directly.
>Newton famously compared his achievements to “standing on the shoulders of giants”
Newton was possibly just taking a dig at his small-statured rival, Hooke. Newton was brilliant, but a shit.
As a programmer I’ve been ‘weeping’ for a few years now.
Programmers, artists, anyone who used to create any form of documentation, translators, there are literally so many.
Either these mathematicians thought it would never come for their jobs, because all of these other jobs were simpler or they've been living under a rock.
Either way, I don't feel for them any more than I do for all of humanity.
When anyone can push a button on a machine and out comes a math result, it still doesn't become theirs or anyone else's until they can internalize it and make it part of their thinking.
"I can’t solve these things, but maybe you people in the future can stand on my shoulders."
Seeing AI being lauded for solving problems like this makes me feel... uncomfortable.
We are feeding all works of the giants that we have all stood on into a huge vat, in the hope to generate something meaningful.
If we can't understand the output, internalize it, or build from the time and experience that a human would have gained from solving the same problem, it feels like a dead end.
When all the problems have been "solved" by AI, what's next? If humans no longer struggle to solve the problems that the previous generation have left behind, how do we progress?
The author mixes "Science" and "Mathematics". Mathematics is not a science. There is nothing empirical about it. By mixing the two concepts, a reader might think that AI is on the verge of solving all of science. Until AI gets good at digging large circular holes in the in the ground, I think Experimental Physics is safe.
Maybe math is more like a science now, though? It's as if ancient astronomers saw the results from a modern telescope. "Why even look at the sky anymore," they might ask. "And we don't even own the telescope!"
Maybe the answer is to look into how Big Science works? There's still plenty of work to be done figuring out what to do with the outputs from these new math-observing instruments.
> Until AI gets good at digging large circular holes in the in the ground, I think Experimental Physics is safe.
Are the experimental physicists usually the ones holding the shovels?
I had visions of large automated warehouses full of chemical and biological components hooked up to science machines to do everything from mixing, boiling and printing to spectrograph and robotic assembly. Smart computers and humans would pick the experiments to brute force with exact billing.
I remember the same doom cycle during my PhD when GPT 4 came out [1,2]. It seemed like everyone in NLP was freaking out except me. A few years later and new CS PhDs are still graduating and joining academia and industry. Much ado about nothing.
Considering I currently live in Ithaca and have a friend doing a Math PhD, so I've heard from him some of the discussions in the department. I think the biggest shock for people is that individuals spent significant portions of their time on some of the problems that OpenAI supposedly solved (I say supposedly because all of the proofs have yet to be independently vetted). I understand that it's a shock, but I'm confident that in time it will be no more of a blip than it was for NLP.
[1]: https://xxcancel.com/mayhewsw/status/1636476184098643968
[2]: https://xxcancel.com/andriy_mulyar/status/163613925780582809...
A blip for NLP? What bespoke NLP research is about anything other than LLMs these days? How many companies are handcrafting bespoke NLP models instead of sending a LLM request? Really confused here.
I’m not sure I’m following… because as I understand it NLP is basically solved now (with transformer LLMs). No?
My friend, who is a math professor, told me that they weep because they are about to become just like us developers: prompt writers and AI output reviewers.
> My friend, who is a math professor, told me that they weep because they are about to become just like us developers: prompt writers and AI output reviewers.
If it was about understanding interesting proofs that some AI came up with, and extracting their essence, I don't think the situation would be so bad.
I see the much larger problem in the now existing career prospects of non-tenured researchers in mathematics. Everybody know how precarious the career prospects in academia and how precarious often the non-tenured positions in academia already are. With the new AI breakthroughs in math, these have in my opinion even worsened a lot.
UPDATE: For a related point, see also pixl97's post: https://news.ycombinator.com/item?id=50104145
I love that we have new ways to solve problems. And it's been hard to accept that my own unique intelligence—which I've spent decades cultivating—just isn't as important as it used to be. I am developing new ways of thinking to better adapt to an AI-enhanced world, but I'm not done with the mourning process. We're all finding our way through this.
What new ways of thinking are you developing?
I object to a few of the assertions made by maths folk in the article- 1st being that Google Translate taught us nothing about linguistics. If you use google translate you learn less about linguistics than if you had to experience learning the languages first hand, maybe, but you can learn form just that output if you are determined to, ad, more importantly, the folks who built it and are still building it are still learning a huge amount about linguistics.
What are the relationships between many languages that become apparent, including code as a language that were not obvious before llms? Translation is fairly solved. The study of how and why languages, not at all.
A hypothetical... suppose AI "solves" (for your preferred definition of "solve") your field and what you used to do becomes useless or near-useless. But you still enjoy doing it and you also get UBI that provides for comfortable lifestyle regardless of what you choose to do.
Questions: (1) Do you still weep for what has transpired? (2) Do you continue to do what you used to do (with optional AI assistance)?
For me: (1) no, (2) yes and I think the same would be true for most people. So I can't help but believe that most of the anguish about AI is far more about a direct economic hit to people's livelihoods than it is about the impact to their respective fields. Which is more than reasonable. But then why not frame the conversation that way instead of beating around the bush?
There is no reality in which everyone gets their basic needs (food, roof, health) without a job.
heck, we have the resources to that now but we don't do it.
I’d be okay with UBI and hobby intellectual work for the rest of my life. But I’m not a mathematician. Many of them probably have more of their identities tied up with their cognitive abilities and social standing.
For many people, the answer to 1 is yes. You maybe happy with our future where we putter around aimlessly as consumers, but some people want to live in a world where they can at least try to do something that matters. Virtually every professional mathematician is motivated by personally making a permanent contribution to human knowledge, no matter how small.
Article refers to Hugo Duminil-Copin, who also did a podcast with Brady Haran [1] about this subject, for him it isn't case of bruised ego, or gatekeeping. He realized that the way things were done were going to change, and it made him emotional, he is not pessimistic or against AI.
[1]: https://www.youtube.com/watch?v=omuJpoV-Ko4
One of the driving forces of math achievement is an internal award (yes, friggin business speak).
The vanity, fame, self-improvement, it's very selfish as everyone does.
Now the fame coming from proving things like Riemann Hypothesis is taken away. Self-improvement? relying on AIs make you stupid. It will be lost. Vanity? Who else don't know how to use AIs? It cannot fill your void.
Now also the most important thing is the communication.
There will be less communications amongst mathematicians at least in person. On paper? maybe but mostly via AIs.
I don't think it's the communication that's lost, it's the motivation. People love to collaborate, but they don't always want to waste time doing it.
It's the same reason you see 'no AI' repo labels: only by forcing some standard on the community can the 'old way of collaborating' continue to exist.
There will for sure be new ways of collaborating, and walled off gardens like you suggest, where communication stops and everyone just shares some final product.
But, in some cases the product must be understood (or demonstrated) before value can be derived, and so collaboration will still exist.
Desire, and the 'shape' of collaboration has changed greatly though. Why collaboration has changed, is a completely separate issue related to economy and how each of us spends our time.
The fame from solving the Riemann Hypothesis has not been taken away. It's still open.
OpenAI didn't have to mass publish these solutions. They did it to make themselves look good. They are ostensibly making a tool for people, to better humanity. Instead, they chose hubris and self-interest.
Letting mathemeticians use these tools to reach the same conclusions would have been far less destructive, and potentially, even exciting. Shame on OpenAI.
> Instead, they chose hubris and self-interest.
Well, you accidentally described a top mathematician before age of 41.
> But tomorrow, it may be the illustrators
I thought illustrators have been out-of-job for quite time, right since Midjourney released. So not tomorrow, but yesterday.
Mathematicians are smart enough to have figured out which way is up. You can debate the stuff outside someone's field not knowing the details but the insiders know what is happening. Ai may not be better than someone with very specific knowledge at this point but it is certainly better than the net. Once it gets optimized for every little super human knowledge, it can do better.
These guys know because they looked at it. Denying it is useless. But maybe some of these guys can figure something new using it and asking it to look for it.
I'm wondering if mathematicians are sort of going through what programmers have been going through recently, really questioning whether their craft can continue. But now it feels like, in the software world, at least from my seat, people can handle much larger scope and work on much more complex problems. If anything, my job has gotten a lot _more_ interesting.
So I wonder if mathematics will go through that too? A period of chaos and doubt, but finding new and more effective ways of working.
Mathematicians are grieving the birth of something that is, in a very real sense, the crowning achievement of mathematical ingenuity.
I never appreciated hard math much because my brain just can't get there. I thought so much of math was much ado about nothing, but now I see the art in math...not in the inscrutable formulas, but in the creation of AI.
Well done, mathematicians. You can now rest from your labors.
> Well done, mathematicians. You can now rest from your labors.
well i think the grieving is because they still have to make rent somehow.
It's got to be alarming. Without a doubt, being not only on the frontier of yoyr profession, but in THE profession that is undoubtedly the most intellectually rigorous and well renowned and respected... It's got to feel pretty awful
2 seconds after AI cures cancer: "I know why the cancer doctors weep"
We are seeing many fields being impacted. Makes me happy to see things like artcraft coming out that directly impacts the big tech companies themselves.
> “They have annihilated my field of research.”
I think they might find comfort in knowing it's not just mathematicians - this is coming for all of us. Computers putting us out of work has been coming for a long long time.... and now it's here.
Mathematicians should web search the arguments when artists were hit by the wave. Scientists in general and people that think humans know better.
This is probably the first time in history deep thinking is being replaced by a machine, but the overall arguments are the same in all cases. Graphical artists saw it first, then programmers, now mathematicians.
No, there is not stopping the wave. No, society won't probably be able to support the same number of mathematicians as before. But yes, there will still exist mathematicians after the wave break, just probably completely different than the old way.
And yes, some people will still try to do artisanal mathematics and say it's better, it probably is, if the artisanal mathematician in question is doing deep creative and out of the distribution work.
Those of us who loved programming have already been through this.
I hate programming these days - back in the day, the cubicle-hell nature of "popular" frameworks was at least offset by being able to think through and solve interesting problems.
These days most of us are stuck in the "endless-review" loop with LLMs. You can't afford to not use it given the inflated expectations. As with all of modernity, productivity doesn't yield leisure - it just proportionally increases your workload.
Hardly surprising that the other side of the Curry-Howard correspondence is now getting hit with this. Math was one of those depts. where slow/deep-thinking was possible (CS was already insane 10 years back - now it's just absurd) - now even this fortress will be broken. Tragic.
If understanding is so important and AI systems can only produce knowledge. Why can't mathematicians continue their work on better understanding?
My take is that it is an exciting time to be a mathematician since the frontier for interesting math problems is about to explode, and without prior art or references, it's green field for both AI and human. Think of all the new discoveries we'll make.
The beginning of this article is decent, the end sounds like a tobacco lobbyist touting the health benefits of nicotine.
> If intelligence becomes less uniquely human, we may come to value more highly what remains uniquely human: our capacity to relate and to care for one another.
Lol. How does the author think relations between people work? (At least those outside the family). Relationships require something that fills them with meaning - a reason why you would want to have that relationship in the first place. Without meaning, no relationship.
I recommended reading this other post that was on HN earlier today: https://thetheorygirlie.substack.com/p/ai-was-great-until-it...
It describes in pretty grim words what happens to collaboration once you have nothing anymore to collaborate on.
> Mathematicians may still teach proofs, argue over what they mean, translate alien logic into human insight, and pass that understanding to students.
This would people to have time to understand and dissect those proofs - it doesn't work if there is a new breakthrough proof every week.
This is such an insidious propaganda targeted at the demoralization of entire professions. Strogatz is an AI booster who "wept". Totally representative!
How much do they pay you? Does OpenAI have bulk subscriptions to your Substack?
> "Earlier this year, Shanmu Jin, a Chinese medical resident, used ChatGPT to solve a problem called Crouzeix’s conjecture, which professional mathematicians had failed to solve for decades."
I note that that these conjectures being solved by AI are named after people, minds knowledgeable and and brilliant enough to come up with the question in the first place and recognize its value. What we have in these AI math solving systems is the equivalent of the chess and go software that can beat humans: something that can adhere to a set of rigid rules to reach a win state once given a starting point. But, as Pablo Picasso said, “What good are computers? They can only give you answers.” These AIs are a magnificent achievement and will change mathematics and coding but can they ask earthshaking questions? Could an AI identify conjectures that mathematicians recognize as a worthy question that will lead to new insights? Where is HAL9000's theorem or the M5 Multitronic's conjecture? Maybe they can someday but I don't see any immediate prospects for it.
Please spare us the "AI will surely keep getting better forever" (unlikely and don't call me Shirley), "moving the goalposts" (I myself haven't set any), etc. non-arguments.
I still remain hopeful that this is a step change in capability and capacity that we can adopt and adapt towards our own purposes. What was taking decades for us to do has been reduced to days and dollars. So while we’re witnessing a forest fire consuming entire fields of open problems in math, the best upside would be finding new problems that come from learning how to work with the new tools.
This is what it seems like so far for software. The speed limit has changed. It’s interesting to explore what that means. Extending the analogy, long ago you could be a race car driver part time; that would be pretty laughable for an F1 driver. It’s a very specialized skill and the optimal athlete is quite different for driving a car than for running, for example. That feels like what I’m seeing in software.
The most effective folks are much faster and better with these tools than average. It’s a different skill set.
I think that formal verification makes Math much closer to code than many other fields. But I’m eager to see the first mathematicians that are dramatically more proficient with the new tools than average.
I mourn the loss of comfy, intellectual, thinking jobs like those of the mathematicians where people could spend time pondering without the immense pressure that would come from doing something like that in a corporate environment.
I wonder how much this is like a tremendous telescope being invented which can see new worlds with utter clarity. We could verify that a planet was habitable... but it wouldn't bring us any closer to visiting it.
This current moment we are in feels like something out of the Remembrance of Earth's Past trilogy, bit instead of humanity becoming super depressed and hopeless about a future alien invasion we are super depressed and hopeless about LLMs destroying all our hopes and dreams.
"I know now why you cry." - Terminator
These guys are still in the early stages of grief. They should look at coders; we've already been there. Coders don't assume coding is going to remain a profession. Why should any other profession be exempt from disruption?
Honestly, there are much bigger fish to fry, like how will everyone pay their bills, and how will we prevent catastrophic AI.
...except it is exactly the opposite of your big brother destroying your tower. Instead, it is your big brother showing you this method using a tool to build many more towers at astonishing speed!
I get the sadness (and, as a software engineer, certainly feel a real existential threat myself) and feeling diminished, but at the end of the day that is all just ego and I very my agree with the end of the article - who cares who came up with it and on what shoulders we stand, as long as it is saving lives and improving our understanding of the universe!
I strongly feel most angst is because Mathematics has become yet another capital intensive game to play. Rather than a noble, purely intellectual practice.
> Think about a world where non-mathematicians leapfrog the field after a few AI prompts. It would be a world with more knowledge. But it might be a world with less understanding.
This seems like a good summary of the article, and I think the answer here is obvious.
So what?
News flash folks: we do not have the knowledge to survive on our own. If a solar flare deletes the electric grid, the first thing that happens is 8 billion people die in the next year.
We survive on abstractions others have built, and we have a global dependency web.
AI abstracting knowledge is neither new or dangerous; if it is dangerous, this certainly isnt the argument to prove it.
Not sure about that title, it did bait me into a click. "Mathematicians are now facing something similar to generational trauma of structural racism born of exploitation, slavery, and colonialism?" https://en.wikipedia.org/wiki/I_Know_Why_the_Caged_Bird_Sing...
But regardless, the detection of breast cancer via AI made me think of phlogiston https://en.wikipedia.org/wiki/Phlogiston_theory . "Phlogiston theory states that phlogisticated substances contain phlogiston and that they dephlogisticate when burned, releasing stored phlogiston, which is absorbed by the air. Growing plants then absorb this phlogiston, which is why air does not spontaneously combust and also why plant matter burns. This method of accounting for combustion was inverse to the oxygen theory by Antoine Lavoisier."
It could be phlogiston. AI is super smart theory states that AI is super smart and that is a single thing can do tasks very efficiently. But it's so smart, we can't understand it, so we humans can't help it, it'll take AI to make it even smarter. That's what's holding it back. But then it'll solve everything.
Or it could be oxygen. AI is super-fast-and-parallel theory states that AI is not a magical monolith but a bunch of pedestrian programs that run fast and in parallel, thanks to hardware (GPUs) that's good at that stuff. But since it's all going so fast and at the same time, something a single human cannot do, humans can't really see how it works. But if we could, we'd probably just see its just doing stuff programs did before. So what's holding it back is that you have to keep throwing hardware at it, and eventually you run into the limits of how fast you can build that hardware or power it.
It all might be stuff humans were better at, when approached one-on-one, but against a swarm it loses. You get a billion doctors together to look at a single mammogram, then tell them if it cancerous, then do that again a billion times with each doctor. Then ask those billion doctors on the billion-and-one mammogram to give a diagnosis. Heck, do that with a billion toddlers. I think either might be able to beat the AI. I don't have a billion doctors or a billion toddlers--frankly I don't know which would be more difficult to handle.
To know if it's oxygen or phlogiston takes probably a demonstration like this "Phlogiston remained the dominant theory until the 1770s when Antoine-Laurent de Lavoisier showed that combustion requires a gas that has mass (specifically, oxygen) and could be measured by means of weighing closed vessels." Maybe the data center financing trouble will be the demonstration that the mass in the gas is just VC-money hardware.
I know why you got a billion cages with a billion birds and a billion bird listeners to compare a billion songs to the few songs we like to hear, and then packaged all that into a single bird-looking thing to make singing-like sounds: So Altman can get that VC money.
Isn’t it deeply exciting that the proofs look so alien?
Isn’t that in itself the new frontier for human understanding?
I would have thought that mathematicians would have found alien forms of maths to be astonishingly compelling, must learn, must know, must understand.
Instead there seems to be a sort of shoulder shrugging lament “we don’t understand it”.
I would barely be able to sleep with excitement at the potential for where this could lead. Like finding an ancient tomb full of answers to our deepest questions along with the promise of more.
How deep does maths go? Is it “solved” or have we just been given tools to delve ever deeper?
Where is their curiosity - don’t the want to find the bottom?
>I wanted to talk to one of the mourners to understand their technological grief. I wanted to know if theirs was a familiar case of bruised ego or disappointment—akin to, say, a boy who spends an hour building a tower out of blocks and watches his big brother smash the thing to smithereens—or something stranger and more profound.
I'll be honest. The response to mathematicians, even this one, makes me concerned about the lack of empathy and honestly just theory of mind of many people in tech. It's not a mystery why people are upset that their field, for many the singular passion to which they've devoted their entire lives, is being annihilated so that a massive company can boost its IPO valuation. It's not "bruised ego" ffs.
‘Tech’ culture has been getting nastier, more vicious, and more zero-sum for years now. It wasn’t even all that long ago that I remember feeling hurt when a friend of mine sneered about “tech bros.”
But I get it now. I see a certain type of guy in an AWS fleece and instantly judge him, round him off to some kind of bully. Harsh, unsmiling, tweaking on stims, telling you to cry harder. Or maybe he’ll open up tell you his theory of how we need eugenic breeding facilities on the moon, or which countries we need to “glass.” It’s gotten so ugly.
I know this seems mean, too. Coming out of nowhere. Strawmanning or whatever you call it. Literally inventing a guy to get mad at. I’m aware of the irony. I don’t know. I guess it’s another kind of mourning, and I don’t know how to express it. I thought tech people were supposed to be like Woz.
I am curious.
Where or what do solving these math problems lead to?
Is there some suggestion that they lead to deeper understanding about something else? Do they solve physics problems?
What’s the benefit? What’s the point?
The interesting answer is we don't know. Many of the math problems that make our computers efficient were developed hundreds of years ago with nothing we could do with them.
It is mostly impossible to figure out what we find when we solve these problems. But occasionally they'll lead to real world efficiency in algorithms we use and it changes the world.
I have little sympathy, since I think it is a result of many decades of complacency when it comes to thinking about why want to people do what they do and instead just enjoying being the ones with the results and money. People who love the process and see the human as inherently valuable won't have a problem. I'm more shocked that there are so many brilliant people who are so results-oriented and don't even have a concept of value outside of that. I'm kind of disgusted by the tears actually
> I have little sympathy, since I think it is a result of many decades of complacency when it comes to thinking about why want to people do what they do and instead just enjoying being the ones with the results and money.
It's not clear from your comment: Are you talking about math professors?
If so, what money? They make a living, but it's not that great. I just checked the salary of two associate professors at my university: $80-85K.
And keep in mind they often start their careers quite late. Often multiple postdocs after PhD. Starting a tenure track position in your mid 30's is not common.
> I'm more shocked that there are so many brilliant people who are so results-oriented and don't even have a concept of value outside of that. I'm kind of disgusted by the tears actually
The whole point of the article is that the person crying is because he loves the process and is worried the human connection will be gone.
This is exactly my perspective as well. Seeing humans as inherently valuable is the key. It's shocking to me that so many people seem to have been reducing humans to the results they are able to produce and now that the results appear to be drying up, their perception of their own human value is going down with it.
Your loved ones have replaced you with more agreeable robots. Now no one cares whether you live or die.
Still disgusted?
> we may come to value more highly what remains uniquely human: our capacity to relate and to care for one another
...under capitalism...
Sure we will...
Of course the other Abundance guy joins in on the AI Inevitability Soothsaying.[1] It really is the perfect vector for the AI sirening. You just take the inevitability and awesomeness as a given. That’s the real point. But you write about the “grief” and the loss of “identity” and psychology—oh my the feelings. See, we are left-liberals and we care so much about people’s feelings. All the investor class and their hype is perfectly on track is about to fuck us the rest of us. But the feelings about people can’t “understand” and “discover” is what matters.
[1] https://news.ycombinator.com/item?id=48387092
ahem
I weep because the money was bad.
I want to sympathize, but most of the whining in the article seems like gatekeepers bemoaning their gates being blasted off the hinges.
Are there any mathematicians who are genuinely excited about this tremendous leap forward in mathematical knowledge? Where are those articles?
> gatekeepers bemoaning their gates being blasted off the hinges.
i think that's 85% of the response from software devs if not more. All of the devs I know who actually like to build have embraced AI and the new capabilities that come with it. The ones that guarded their little corner of code proclaiming only they, and their inner circle, have the power to comprehend it are the ones crying in the corner.
Getting those fields wiped just shows how unnecessary those fields where in the first place. I'm a programmer. I am the adapter between a stakeholder and a machine. I am just needed because the stakeholder lacks the knowledge to tell the machine what he wants. If he can use this new fancy adapter called Agentic AI now I happily quit my job and go on finding something that makes more sense in the first place.
The same goes for math.
Let's find some things that bring value other than just the price of a stock.
Broken take, with out this trail of mathematics that lead us here we'd have never reached this place. You think multi dimensional matrix math comes natively to humans?
At worst its time is past, but even that is unlikely.