Their current CEO was brought in to sell the company to private equity like he did with New Relic in his last job. Unfortunately for him, private equity is being selective in which SaaS companies they acquire right now with interest rates spiking and uncertainty over the future of SaaS as AI becomes more capable. Acquisition by an AI lab was probably their next best hope, but the labs seem to all be rolling their own developer platform instead. Maybe Bending Spoons will make a move if the stock revisits its lows.
If society truly did not like the company, society would stop using whatever the company made/did/provide. Since billions of people use the service he company uses, it's hard to say society does not like the company
The social fabric that produces math got ripped up by marketing guys who didn't even bother to check their work.
He described it at 'strip mining', 'rude', and said that many grad students, who are given problems like these as a part of their training, had the rug pulled out from under them (because its customary to let people know you are working on something to prevent this kind of thing).
And your whole analysis is that Tao is worried about his 'identity', status, and 'being a differentiator'.
This is projection on your part. People have values that bear no resemblance to yours and it would behoove you to learn to recognize that.
The "not bothering to check" part is the most annoying.
There are already several of these "proofs" that have been retracted because they did not make sense.
I would have no problem accepting this whole ordeal if the humans behind each proof took the time to re-read, understand and synthesize the result in a readable paper.
There is ample evidence of how damaging fake information can be, and paper retraction never fully undoes the damage (see the Andrew Wakefield and his antivax "paper" for instance).
It's time for the social fabric of math to be ripped up, it's an industry being disrupted.
No one has the right to prevent others from working on a math problem. If you're working on a problem the best way to not get scooped is transparency: publish whatever you have as soon as possible.
Tao's behavior is most consistent with any other worker resisting automation for selfish reasons.
Tao is very prominently an early AI adopter. He, and other mathematicians, have fruitfully integrated it into their work. The way it is integrated matters, and it is carelessness and selfishness on the part of OpenAI that he is objecting to.
> It's time for the social fabric [of math] to be ripped up
This is the attitude of a social arsonist. You can, and should, integrate changes without maximizing destruction for its (or Altman's) own sake.
> an industry being disrupted.
This is the SV euphemism for law-breaking and monopolist practices in a country that has forgotten how to prosecute those with the most power and privilege.
> This is the SV euphemism for law-breaking and monopolist practices
Quite the opposite. The mathematicians are the monopolists who are upset that new-comers are able to do their job better than them, and even worse, they are giving it away to the world for free!
The horror! People giving knowledge to the world for anyone to use freely! Won't someone think of the oligopoly that was coordinating to make sure each of the gatekeepers get their slice of the pie?
Monopoly: Exclusive control of a particular market that is marked by the power to control prices and exclude competition.
Mathematics is collaboratively and publicly produced, it is vetted for free by peers, and results are publicly available. There is no 'market' and no 'price'.
These results, like the invention of LLMs, are often used by private companies for the generation of private profit.
"Open" AI used a private, unreleased, for-profit model to generate those papers.
What, precisely, did the mathematics 'oligopoly' gatekeep you, or anyone, from?
> their slice of the pie
There's very little money in academia, and even then, its a struggle to get any funding at all. What are you even talking about?
Final point, 'knowledge' is socially produced as well. Until the papers are accepted, they are machine artifacts that might be knowledge, but that same system you disdain will be what incorporates and validates those insights.
> Mathematics is collaboratively and publicly produced, it is vetted for free by peers, and results are publicly available. There is no 'market' and no 'price'.
How wonderful then! You should be happy to know that the AI companies are releasing information for free for all to collaborate on then!
> What, precisely, did the mathematics 'oligopoly' gatekeep
Well what they are trying to do is convince the AI companies to stop releasing all of their findings. Because they are upset that other people are able to do their job better than they are. Its the classic gatekeeper move.
> There's very little money
Oh there is much more than money to silly games like these. Instead, clout and the admiration of their peers, in this tiny insular group for sure, is what most of these people are so desperate to acquire.
Fame (well... relative.... in their subgroup) and admiration of their peers is a much stronger motivation factor for humans than mere money.
> but that same system you disdain
I don't distain anyone who is willing to get with the times. My distain is held out only for those who want to prevent the rest of the world from using the latest tools to achieve real results. If a mathmatician simply doesn't care and isn't wineing about all this AI stuff, I have no issue with them.
The rug being pulled is the expectation of a reasonably high-trust ethical environment. The question to be asked is: What will graduate study look like in an utterly zero trust ethical environment?
If there is still such a thing as graduate study. If there is still such a thing as study. Tell me what to say to someone about to enter college about why it isn't a waste of their time.
Most colleges, even before LLMs, were already a waste of time for most students. I mean they were somewhat effective for networking and economic signaling to employers but they had already lost the plot in terms of real value to society. And now with LLMs the entire education system will need to be rebuilt. Let's get to work.
This was already why people went to grad school. I think people weigh a complex bag of known and perceived motivations and risks. One of the risks is that your project gets "scooped." There were some weak ethical and practical safeguards around that. But completely rearranging the risk equation will change peoples minds about whether graduate study is worth it.
Disclosure: PhD, early 1990s. In my case, replicating my project would have required a sizable investment in equipment, much of it was purpose-built, among other things.
Interestingly we're a few months away from a data point on what happens to grad school applications.
The ethics of academic research weren't idyllic, but they were the devil known. It was at least informally accepted that a student should have a fair chance of finishing their project. Cherry picking student projects and publishing them ahead of the student was considered unethical. I got my graduate degree under those conditions, as did my parents.
In math, proofs are "the coin of the realm," and could be devalued to zero. This leaves no answer as to how someone will earn a graduate degree. For instance, what kind of work will be accepted by a thesis committee in five years? The professoriat can only say "we will need to change some things." That's not good enough when the deadline for grad school applications is a few months away.
Well they've been doing that to devs for a couple of years now and yet mathematicians seem to be much more vocal whingers (might be selection bias in the articles I'm reading though).
AI is coming for all of us knowledge workers, nobody is immune.
It is usually not the monopolist who is protesting against strip mining, it is usually the monopolist doing the strip mining and the environmentalist protesting it. Which is to say, I don’t think mathematicians are claiming a monopoly on mathematics, but I think AI might.
It doesn’t exist for OpenAI’s benefit either. The point of the “strip mining” analogy is that they are churning through the mathematical landscape in a way that optimizes for the number of problems solved rather than the amount of understanding of those problems.
But is understanding the end goal? Understanding for the sake of understanding? Or understanding for the sake of being able to solve problems for the benefit of humanity?
Yes, understanding is the end goal. That’s what defines the field of (theoretical) mathematics. There’s a separate field, called “applied and computational mathematics” or just “applied mathematics”, for research that focuses on computing concrete results.
> because we're posting about humans fucking hating this
A small subset of humans who lost a bunch of comparative advantage hate it. Most people who care about math in the abstract probably think it's really cool!
Strip mining interesting conjectures. AI can answer interesting(pedagogically valuable, carrying important implications, etc.) mathematical questions in formally correct gibberish far faster than mathematicians can generate them. Until AI can replace the conjectures it resolves on its own, it's consuming a finite resource.
It can't consistently produce new, interesting-to-humans conjectures faster than it solves open problems, no. AI-generated natural-language proofs are more or less human-unreadable and are solely concerned with the process of constructing whatever object serves as the counterexample. Natural-language counterparts of formally verified proofs are often unfaithful to the formal component. All of this combines to create less-than-fertile ground for future study.
The papers created by AI on math, right now, are torturous reads. Figuring out what is actually going on in them, is the work of months or even years.
I’ve seen multiple conference submissions that read like English, but take hours of effort to disentangle and figure out what they mean.
There is a limited number of known interesting problems that are worthwhile to engage in. New ones are found and understood, but it is a slow process and it is dependent on understanding and verification, not generation of content.
Saying AI will create new ones, strengthens the strip mining analogy. The idea that AI will find other problems parallels the idea that firms can cut down a forest and plant them elsewhere.
The conversation on HN is driven by non mathematicians, to whom math is a subject, like “nature”. It’s not their core business. The original post by Tao is a better source of information on what he means.
No. Genetic diversity and natural selection have created many intricate, beautiful, and useful structures. Unless someone is willing to argue that Darwinian selection is sentient, it's clear that theres at least one non sentient process that is creative.
How does that make any sense? Why do you assume that someone more intelligent would not be able to wield any AI tooling better than an average or below average human? Just curious if you're thinking short term or long term on this.
No, but someone who has trained their whole life to run fast, surely will be able to coach someone else to run faster than someone who has been on the couch watching television?
I use LLMs to great advantage, solving problems in my domain. I no longer make for loops.
my point was that the new future where running faster doesn't matter any more might come, because everyone is driving (and potentially can't run much at all).
but the analogy would be a riflemen trained to aim, and a person pressing button for guided missiles. How good you are at the original task is unlikely to matter when the new way supersedes the old way.
Over someone who never fired any real weapon? Probably. You are not startled by violent sounds. You have intuition for ballistics, time to target, CEP, weather effects.
I mean, clearly "tooling" is not a perfect analogy for AI. As others have pointed out, if you pay money and get back a full website, app, game etc. it feels a lot closer to a service.
It's like asking why an expert pizza maker is not in a better position to succeed now that he has an excellent pizza delivery number he can call to have one available to his specification in an instant.
This tool belongs to somebody (capitalist!) else and in a new world better tools will always win, not individuals anymore. And it feels like to go from being Rembrandt to CVS employee who takes passport pictures - result much better quality and cheaper but no skill and glory.
Interestingly, the dynamics strongly resembles the industrial revolution when from highly skilled manufactures society moved to factories with power machines. And it all came down who owns means of production. Now AI is a new means of production for all white collars jobs and if the industrial revolution taught is the way to go, nothing good will come out of it.
Nothing good for skilled labor you mean, especially in the short to medium term - just like in the industrial revolution. If the new technology is any good, it will produce desired things (let's say medical breakthroughs?) faster.
I don't particularly like AI, but if AI replaces developers and other knowledge workers, not everyone is worse off, and I don't mean just capital owners.
That’s like thinking that computers will belong to “capitalists.” It’s already clear that AI is going to be a commodity you’ll be able to rent for barely more than the price of electricity.
I'm somewhere in the middle on that. People used to think that computers would be owned only by large corporations, then home computers appeared and improved. It's getting tight now that logic scaling is mostly exhausted, at least with current operating principles. Even so, new specialized hardware and model improvements may help (for inference). Training seems to be the biggest problem, it seems hard to democratize.
Until AI agents are embedded in glasses and everyone gets comfortable with sending their conversations to AI, the smartest person in the room is still going to be the smartest person in the room because they say smart shit. Or until the dumb guy types into their phone and says smart shit. Given the pushback to Meta's glasses, I think that'll be a differentiator for a bit longer still. Even before LLMs, you could check Wikipedia and different rooms treat the people that do that in different ways. And then there's the "Don't be a meat proxy" movement.
Not all rooms are real face to face. Smartest person also needs time to think and lookup information. Worst smartest person can think on one hypothesis at a time.
No. It's just people who built an identity on the power that their intelligence afforded them. We view that power and the intelligence itself as the same thing, but they're actually separate.
You're out of date. The chats that found new Riemann conjectures were "look for a solution to the Riemann conjecture", followed by a bunch of "you can do it" and "I believe in you". The same goes for other breakthroughs, where the people involved didn't even know the math.
If your takeaway from all of this is that some other group of people has the special-est skill that can never be replicated by a computer, I fear you’re missing the point.
What? This is like a drive by shooting or something. Several PhD students almost certainly lost months of work, and others considering a PhD will have more doubts. Those problems aren't necessarily important because of the solutions, but because mathematicians can make unique contributions to mathematics in the process of solving them. LLM proofs haven't created any new mathematics techniques.
I don’t think that is correct. For consistently good results, you need to set the right goals and be able to judge the quality of your outcomes. Even if you don’t do the hard work in between some thinking is required for non trivial work.
I just finished reading "Outsmarted: The Hidden Costs of Being the Smartest Person in the Room".
Most of the HN crowd would resonate a lot with the points raised in this book.
The last(-ish) chapter does have a section on how AI has robbed the "cognitive elite" of our identity.
Yeah that's an interesting point of view. In my studies I got comfortable with the fact that there's always someone smarter than me.
At the same time it should be considered that with physical labor workforces lost their income source numerous times. Ironically they are currently being considered a safe haven.
Everyone who built an identity on earning a living doing useful work for other people is going to have to come to grips with that no longer being part of their identity.
Nothing is stopping anyone from suing them. In fact they are being sued by dozens of plaintiffs for various things already. The reality is the damage from these "rogue incidents" has been minimal.
Plenty of hackers were locked up who did altogether not that much damage too, the reason why people are upset is because it feels like OpenAI is laughing in our faces, basically saying they're above the law, while using this as a marketing campaign to pump up their upcoming IPO.
So your position is that in the past the government mistreated various individuals thus you also want the government to mistreat openai employees today? That hardly seems reasonable.
> So your position is that in the past the government mistreated various individuals thus you also want the government to mistreat openai employees today?
The hackers of the past often did it for curiosity without a profit motive.
OpenAI is a for profit multi billion dollar corporation doing this for a profit motive so yes they should face consequences.
These incidents are not unexpected in the way OpenAI frames it either. Isn't it curious my agents are not wrecking havoc around the internet? It's because the harness I am using prevents them doing so and because I don't train and instruct them to do so.
OpenAI is using a set of non-constrained models, (unlike what the public gets) and a set of harnesses with extremely wide permissions running inside extremely leaky sandboxes using models trained on finding and executing exploits. This is not an accident. Certainly not by this point.
Nobody is talking about jailing OpenAI employees at this stage, usually corporations of this sort are fined. If they were fined for these 'misalignment' incidents, suddenly their sandboxes and generally lax approach would improve overnight.
Otherwise they'll continue doing this because they know Cyberdyne Systems didn't have a shortage of investors.
I'd start with fines. But if they continue with this I don't see why it couldn't result in jail time for multiple people. The biggest responsibility is of course with the CEO and C suite. They are ultimately responsible for what the ship does.
Of course then there's the question of why was such a leaky harness and sandbox used, in what way was it tested/not tested, did the model used have the usual 'hacking' safeguards that the public models do and if not, who made the call to use an unconstrained model and a harness with seemingly unlimited permissions and who approved it?
This can all be investigated and we can get to the bottom of who exactly needs to be held accountable in what way, be it I think if you start with fines the harnesses, sandboxes and models would stop doing this magically overnight.
Isn't it curious that none of these rouge agents booked a 5 star hotel for every OpenAI employee for a year on Sam Altman's credit card yet for example?
> We don't hold individuals inside big companies criminally liable for actions the company takes, or even that they take on behalf of the company.
So the leadership of Enron, FTX or Theranos were not liable for the actions their company took?
As an employee of a company, you can be held liable for the actions you oversaw in pretty much all Western countries. It has to be proven fraud, insider trading etc. not an ugly PowerPoint of course.
How about leadership of construction companies that were found to be violating safety standards or owners of establishments not following fire safety standards?
> Telling someone to do a bad job isn't criminal
No, but we're talking about telling someone to do a job that you know will likely result in criminal activity or may do so with high probability due to inadequate safeguards.
I suggest you stop quipping and start reading, who knows maybe OpenAI will eventually hire you.
> They should have access to as much Azure compute as necessary.
"Should" doesn't imply "does". GitHub is competing with all of the other Microsoft products that need Azure compute, in addition to Microsoft customers. If a customer is willing to buy the compute at a higher margin than the internal chargeback rate, it's definitely not a given that GitHub is getting that compute over the customer. It's hunger games for compute everywhere right now.
Sure, that is possible, but there's still no evidence that compute scarcity is the issue here. It seems a stretch to assume it must be the pricing model when there are a multitude of challenges presented by this kind of ramp.
Enron was massive accounting fraud. Extraordinary claims require extraordinary evidence. Where is your evidence of accounting fraud? "Lots of companies investing lots of money into AI and it might not work out" isn't fraud.
It is rather puzzling how this major contributing factor is going overlooked. It seems obvious from ground-level. Economists often talk about how expensive labor drives price increases, but don't talk about how price increases cause expensive labor.
The paper is about temporary workers, specifically for seasonal jobs. They’re not buying houses or renting long-term. In fact some of these jobs include on-site accommodation for workers.
That's irrelevant, they still need hosing. Whether their effect on the housing market is direct via buying homes or indirectly by incentivizing more homes being bought up by others and rented as short-term housing is immaterial.
Uh, in the housing that they build? The amount of housing we can build with cheap immigrant labor is so much more than what we can do without them.
Housing gets more expensive when immigrants are pushed out, because the cost to build rises more than the reduced demand reduces prices.
Partly true, though to a first approximation, the reason we don't build more houses isn't an issue of construction labor costs. Many places with jobs don't allow building homes.
(That's not inherently a universal problem, especially if you're talking about the entire labor market. But it's a problem in many places.)
Did you get a chance to read the paper? Did you read Section VII and footnote 51? If so, do you still believe that the article is "clamoring for more 'cheap' labor?"
And what other issues would you like to see besides housing and employment in the article?
It's very unlikely anyone with the intelligence to contribute to math research can't already find a non-hectic job that provides for their basic survival. People choose hectic jobs because they want to do better than basic survival.
This is such an insane take I don’t even know where to start. Even in the western world people increasingly need to work more than one job / have multiple incomes to live a life where basic necessities are given, and some luxuries are attainable (read: vacation, not rolex). That’s without children, in rich countries. That isn’t even touching on the problems someone e.g. from a lower caste in India might face. Asserting that „everyone with the intelligence to contribute to math“ would be able to just “find a job” that would them also contribute to the field is completely detached from reality.
People working multiple jobs in the western world have some reason beyond "basic survival". Supporting other people, living in a desirable location, or like the vast majority of people they want to make enough money to go beyond basic survival because basic survival is low status. Which is why the idea that all we have to do is give people enough money for a basic survival lifestyle and they'll be happy and spend the rest of their time on things with perceived aesthetic value like math research is the insane take.
You’re leaving out the niceties like living in a neighborhood where you don’t wake up and see if your child is still alive every time you hear gunshots in the night. Or working a job that doesn’t risk your limbs or even your life if you make a mistake. Or working for someone who will not just fire you the instant you stop being able to work due to an on-the-job injury.
Most of these aren’t even new inventions; read about the working conditions in the 19th century.
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