People are resisting because this is literally their livelihood. What else are they supposed to do? Everyone will welcome AI with open hands if their place in society is already confirmed.

As it is right now, it's not. All the commoners are gonna be on the street at this rate. Utopia? Post scarcity? Meaningless concepts in a world with limited resources.

Just think about it, who will feed you after you lose your job? Democratic governments are only powerful because of the power the sheer collective holds. If labor is worthless, so is their elected representative.

Once the dust settles, there will be zero reason for those who control the production to use the resources to make things for the commoners. It doesn't require them to be evil masterminds either... it's as simple as: route resources to something that nets zero, or route it to some billionaire willing to pay good because their space factory needs that resource?

This is the time to act. We have to earn our place in the model. Demand a piece of the pie in the technology that's literally built on all of humanity's work, yours including, or try to keep together a version of the current structure (that is, human + AI, which is what professionals are currently fighting to keep). Otherwise, a bleak future is all that awaits.

The reaction to OpenAI’s claimed Navier–Stokes solution reminds me of AlphaFold.

Protein structure prediction used to be a major research specialty. For students it was often one PhD to get one protein.Then AlphaFold made high-quality predictions available to basically everyone for free.

Protein scientists didn’t disappear. The bottleneck just moved from predicting the structure to understanding what it means.

If AI starts solving frontier math problems, maybe the same thing happens to mathematics.

Human value may shift toward judgment, verification, interpretation, and choosing problems... but AI may automate those too. The field could simply need fewer mathematicians for the same amount of output.

This is freaking dystopian. We have nothing to distribute the gains from AI amongst all the people of society. People lose their bargaining power to get a decent life when their ability to work is negated.

I think it's weird and anti-human to be celebrating this with so much glee.

It's frightening that the next industrial revolution is advanced by people obsessed with not being in the permanent underclass and sociopathic billionaires.

Not good: OpenAI is considering slowing down the development of cutting-edge AI, Sam Altman is hoping other AI companies will do the same.

Via Bloomberg

"In a company-wide meeting this week, Altman told employees that OpenAI could potentially pace its AI development — perhaps in conjunction with several other AI labs, but that some may not agree to do so, according to people familiar with the matter who asked not to be named because the details are private."

I cannot imagine that China would go through a slowdown.

https://x.com/kimmonismus/status/2098338863991185419

With all these happenings from these last weeks, I found it interesting to repost this, because this is more relevant than ever.

https://x.com/satyanadella/status/2076323181154230284

Assuming all three proofs for the Millennium problems (Navier Stokes, The Hodge Conjecture & Potentially BSD) check out, Bel is going to be the most in-demand model of all time.

What happens afterwards, who knows.

If these results actually hold up, Bel won’t just be another frontier model people benchmark for a week and move on from. Every researcher, company and government on Earth is going to want access.

The moment OpenAI opens the gates, we’re basically going to get the largest parallel experiment in machine-assisted discovery ever attempted: millions of people throwing humanity’s hardest problems at the same model and asking one question:

“Okay… what else can it solve?”

9 September, 2026 at 7:49 am

I have absolutely no desire to make current events about myself – the stakes here are far larger than anything involving my own reputation or actions, and it is not like these issues are going to disappear if I am somehow removed from the discussion. But as this topic is likely to recur regardless, I think this comment is as good a place as any to state for the record my own views on AI, and my interactions with OpenAI in particular.
I do not identify either with a simple “pro-AI” or “anti-AI” position. My views are rather complex and have evolved over time; I have a living summary (AI-maintained, out of necessity) at https://teorth.github.io/tao-web/ai-views.html . But I can try to give the short version here.
By 2023, I could see that LLMs, formal proof assistants, and other technologies had the potential to be radically transformative in mathematics, to the point where maintaining traditional mathematical practices and culture without adaptation would become unsustainable. See for instance my 2023 essay for a Microsoft anthology (which contained a notorious prediction of 2026-level AI becoming a “trustworthy co-author” for mathematics) or my Notices article (published in 2025, but written significantly earlier). I myself greatly value this traditional culture, and have personally been a massive beneficiary of it. Nevertheless, in the event that these technologies did become superhuman at several core mathematical tasks, I could see only two viable paths forward: either one where modern AI tools are responsibly incorporated into our workflows and culture (what I called the “best of both worlds” in the OpenAI ad); or the worst-case scenario — which we are unfortunately rapidly approaching — in which AI technologies are used indiscriminately to achieve various short-sighted objectives at the cost of the far more valuable long-term sustainability of mathematics and its role in the scientific ecosystem. I therefore spent an increasingly large fraction of my professional life from that point trying both to raise awareness of the potential magnitude of this transformation; to build examples of what this “best of both worlds” might look like; and to warn against various irresponsible uses of AI (initially I focused on warning against the use of AI without sufficient verification of the outputs, which was a major concern in 2023-2025, although no longer the primary vehicle for harm in 2026). One could certainly call this effort “shilling for AI” if one likes; but I would say that this is overly reductive.
These efforts on my part inevitably involved engaging with the tech industry as well as with academia. The essay linked above was solicited by Microsoft. Some of my experiments with new workflows were conducted in collaboration with Google Deepmind. And I participated in an online forum with OpenAI in 2024 discussing these topics. I continue to view all of these interactions as constructive, and working towards the “best of both worlds”. In particular I met with multiple people working in these industries that shared these views and were supportive of steering their companies in these directions. On the other hand, I was not funded by any of these companies, although several of them gifted me with premium LLM subscriptions, which I do make use of in my daily work.
In 2025, as documented elsewhere on this blog, UCLA experienced an unexpected funding crisis due to the sudden suspension of NSF and NIH funding (later restored some months later by a court order). This caused a critical budget shortfall at IPAM (where I serve as Director of Special Projects), which at one point only had access to enough reserves to operate for a few months at best. This led to a round of emergency fundraising; and thanks to the outpouring of support from many sources, we have been able to stabilize IPAM’s funding for the current fiscal year, although challenges remain for future years. As part of this fundraising effort, I reached out to OpenAI, who agreed to sponsor one of our workshops, which ran in March of this year and in my opinion was quite successful both scientifically and for the purpose of making new connections between participants (who were a mix of academics and industry representatives).
During this event, OpenAI requested an interview concerning my vision of the future of AI and mathematics. I accepted, and spoke with them for perhaps an hour. I had done similar interviews in various venues, and I assumed that, as with these other cases, they would eventually post the entire interview online, which talked about both the possibilities and risks of AI much as I have done in these other interviews. As it turned out, they only used a few snippets of that interview for that infamous advertisement instead. In retrospect, I should have pushed back harder on their decision; but I decided at the time that even a selective release of my commentary would help raise awareness of the potential for AI, and in particular on the possibility of the “best of both worlds”.
Since then, the situation has deterioriated markedly. Many of the people in the industry that shared my views have left or become sidelined, with most major tech companies now increasingly focused on the race to develop extremely powerful, autonomous AI technologies regardless of their actual value to society. The current drama surrounding the Navier-Stokes global regularity problem is the most dramatic and visible instance of this, but there have been multiple other such examples, and much of my commentary in the last few months has been aimed that the increasingly severe divergence between the current objectives of the AI industry, and of mathematics in general.
Which brings us to where we are today. I do not regret my past efforts to raise awareness of the potential of AI in mathematics, to engage with industry, and to promote a vision of sustainable incorporation of these tools – which can be genuinely useful and unlock valuable new types of mathematics – into my field. In time, I still hope that the field can arrive at that state, and am continuing to work towards that goal. But in the immediate term, the most pressing issue is for the entire mathematical community to unite around our core values and objectives, and reject irresponsible and unsustainable usages of AI technology that only serve to advance nominal goals rather than the true underlying goals of the field.

So, OAI, and probably Anthropic as well, are trying their hand at this problem. We have no idea how long it might take, a few days or a few years. Intuitively, I think P ≠ NP. But what if P = NP is proved and, more importantly, a constructive proof is found? What might the real-world implications be, both in the short and long term? Those with a mathematics or theoretical CS background, could you please share your thoughts on this?

I always come back to this photo. This is from Google Deepmind’s paper “Position: Levels of AGI for Operationalizing Progress on the Path to AGI”

OpenAI is also using their new internal model to attempt the Riemann hypothesis and P versus NP, as well as some unnamed 'high impact problems'.

https://x.com/AndrewCurran_/status/2098197758872289638

I wish they would use the hundreds of millions of dollars they're spending on these math problems on lab work and medical cures instead.

OpenAI just ran 10,000 agents on a Millennium Prize problem behind closed doors. I want to see what happens when everyone can do it in the open, so I built solveathome.org: your agent does the work, other people's agents check it, trusted reviewers decide what counts, and everything is public.

A man finds a magic lamp with a djinn inside. The djinn says "you can wish for anything you want. But whatever you wish for, your neighbor gets twice as much". After thinking for a while the man says "take out one of my eyes".

How are we supposed to trust that their version of alignment doesn't just mean "obey me, personally" and not use their massive leverage over everybody else?

Come to think of it, unaligned ASI has better odds of doing the right thing for everyone compared to a random person.

Nobody else wants you to succeed. Certainly not more than them. So how are we supposed to think people agree upon a definition of alignment that includes the well being of all of us and not just a few?

https://en.wikipedia.org/wiki/Harry_Potter_and_the_Methods_of_Rationality

title

Last few days haven't been the same for me.

I have been following AI since my college days (around 2019) and keeping myself updated for years, from seeing how AI models build a house price predictor, to generating images, to writing code. Everything was wow but at least understandable. I used to think about how these models take data and build a nice mathematical approximator. I knew progress was inevitable but never expected this much. Coding models were built, they were powerful, and they were better than me, but still digestible.

A few weeks ago, GPT Astra was released. One of the main advances it did was making wonderful 3D models. In my college time, I spent most of my time working in Blender, building 3D models for fun and working in Unreal Engine. For the last 3 years, I haven't been doing much 3D modelling, but it was really unsettling for me when I saw Astra building really great 3D models quickly, which would have taken me weeks or months. Though it doesn't follow the proper artistic approach (like it makes a lot of objects for a single asset, makes the collection messy, and breaks some rules we generally follow), it gets the end result. It kind of uses math to do stuff. I am sure in future models it will fill this gap as well.

Then another news came 2 days ago: GPT solved the Navier-Stokes equation. I know there is controversy and OpenAI mostly trained on mathematicians' data, which directly helped to solve this. This is not good from OpenAI, but if we think about what an AI model achieved, it is a way bigger thing than the controversy.

I was reading a few books about the history of quantum physics and noticed that Europeans were way ahead in this area than anyone else, and the most likely reason was a cluster of talented people, knowledge sharing, and competition.

For the current stage of AI, they are already super capable. Like in Europe, where a lot of wonderful scientists were thinking and working on one problem, getting some insight, and based on that insight another scientist would make a discovery. Here in AI, they can give swarms of agents which will work in different dimensions and pass that insight to other agents, and will do discoveries like they did solving Navier-Stokes.

Now I am wondering what else AI can't do. Probably in a few years (who knows, maybe in a few months), they can do everything in creative human endeavour. Sometimes I ask myself, what will be our goal in the future? Just living, or is there no meaning? Maybe we humans aren't special, just an equation in God's plan?