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The cruelty has been puzzling me. Under almost every post which recounts the anguish of someone seeing AI models becoming shockingly good at their own craft, there is a stream of comments telling the poster to, essentially, accept their own obsolescence. If the poster calls for this development to slow down, the response is to stop standing in the way of progress. If the poster wants to nuance the picture of the machine god steamrolling everything, reply guys call it “cope” and “cringe”. Most recently, this has been happening in mathematics with the field’s shocked reaction to the deluge of AI-generated proofs, but similar dynamics have played out for musicians and visual artists, and to a more limited extent for programmers. These people seem to be cheering for the machines rather than humans. But I don’t think it’s as simple (or as extreme) as anti-human sentiment. The more charitable read is that most of these people really believe that this represents progress. They are excited about scientific and technical progress, and don’t want old farts like professors and other credentialed types to stand in the way. Let’s unleash machine science, and if the professors and intellectuals don’t like it, they can find something else to do! But this is a perverted idea of progress. What good is a proof of the Riemann conjecture if there is no one who understands it? And not just a single person: you need a whole community of people to understand it and then gradually think about what it might lead to. Maybe the result will contribute to a better encryption algorithm, or a better understanding of quasars, or something else. But this requires diffusion of understanding through scientific communities. A proof of the Riemann conjecture by itself is meaningless; to me, or to the vast majority of people out there, it’s just a bunch of symbols that we can’t read. The same thing can be said for other types of research: say, for example, that your AI system deciphers some cellular mechanism that could help with a cure for cancer. A whole network of experts is then needed to do all the complex science and innovation that helps translate this into a cure, test it, and so on. The paper itself would just be collecting digital dust unless the right scientific communities were there to build on it. Now, where do all these experts and their communities come from? From doing research. The only way we know of making people understand the frontiers of a field of knowledge is by trying to advance it, which must come with a real chance of succeeding and being recognized for it. It’s very hard, not to mention boring, to understand the minutiae of some arcane topic if you are not working on producing new knowledge there. If you fully automate the production of results in some discipline, you will also cut off the supply of experts who can understand it. People who have never participated in research may not understand this. If that’s you, try reading a recent paper in a field you know nothing about: category theory perhaps, or carbon nanotube synthesis, or cecidology, or loop quantum gravity. Faced with pages of mysterious scribblings, you can ask Claude or Gemini to explain the paper to you, but then the terms used in the explanations will need to be explained again, and so on. You will find that, in order to actually understand the research and its significance, you will need to understand the whole research field. Then there are those who do understand the role of expertise and the difficulty with which it is cultivated, and still ridicule those who are less than enthusiastic about the AI-driven disruption/destruction of whole research fields. Wherefore? What are they thinking, really? Let us again try the most charitable interpretation. Maybe they believe that we will not need anyone to understand that proof of the Riemann conjecture, because some complex sequence of AI systems will take us all the way from a proof in fundamental mathematics, via all kinds of research, development, and design, to a finished consumer product shipped to your door. This would imply end-to-end automation of much of the economy. I guess some people are really worried that something like this might happen, and therefore want to pre-empt it by acting as if it were already a certainty. This, I think, is the gist of statements like “everything will be AI anyway”, which I’ve seen cropping up with alarming frequency. Submit to the machine god before it arrives, a form of anticipatory grief. Abandoning agency early makes you look like you have situational awareness. “Coping” is uncool. I get it, but cynicism is always the easy choice. It’s also the cowardly choice. Let’s not be cowards. We have agency here; it is a given that technology will advance, but the exact way in which it will advance is down to all of us, and how we adopt this technology in society is something we can and must decide on together. Finally, there are those who have thought all this through, and still welcome the wholesale replacement of human cognitive work. Those for whom it would be a good thing that some sequence of AI systems does all the thinking, so we don’t have to. Who would think this? Well, clearly, someone who doesn’t much enjoy thinking. But I think it’s more than that. I think that there are people for whom the devaluation of expertise would be a good thing. Those who “have had enough of experts”, as Michael Gove said of the British people in the campaign for the Brexit referendum. Those who think these clever know-it-alls should be put in their place. They think people who have spent much of their lives specializing in some narrow topic should not be given all that respect and influence they seem to have now. This is called anti-intellectualism. And that’s where the cruelty comes from. I can’t know what’s going on in their heads, but when I see people telling mathematics professors to go get a real job, as if their jobs would somehow be less real than those of massage therapists, real estate agents, or police officers, I call that anti-intellectualism. Much the same as for people who would rather take health advice from a podcaster than from a medical doctor, or who would happily see a news show host rather than a decorated general in charge of the military. At the extreme end of anti-intellectualism, we have the Cultural Revolution and the Khmer Rouge. I hate anti-intellectualism. I think our society should incentivize people to study hard, think deeply and originally, try to push the boundaries of knowledge, and talk freely about it. I think those who spend their lives specializing in arcane topics should be respected and protected. Yes, it goes without saying, I am an intellectual. A tenured professor even, the worst of the worst from an anti-intellectual’s point of view. So you would expect me to defend the experts and intellectuals. But let me make a non-self-serving argument: humans will always compete. That’s human nature. Would you rather live in a society where the smartest people compete in understanding the mysteries of nature, developing complex technology, and producing beautiful art, or in a society where the smartest humans compete by accumulating money and/or simply by fighting each other? As I have written about before, I am worried. I am not worried that out-of-control AI will kill us all or even that it would put us all out of work. There will always be some kind of work for us. I am worried there will be no place for us in advancing knowledge and understanding the world. I think that the defining question of our time is how to avoid this fate. It’s not a matter of my own job, or yours; it’s a matter of the purpose and dignity of humanity as a whole. Big words, I know, but I think they are warranted, and I don’t care if the cynics call it cringe. So next time you see someone complaining that AI is steamrolling their field of expertise, don’t join in the heckling choir. Don’t be cruel. And don’t assume that someone who has devoted their life, or at least their career, to furthering knowledge wants to stand in the way of progress. Instead, try thinking constructively about how we can work together to ensure that human experts and intellectuals can float on top of the AI wave rather than be drowned by it. Do we have a deal? Alright, thank you! Now I will go back to thinking and working on AI, meaning artificial intelligence, not anti-intellectualism.

Language models learn style and content jointly. In new preprint with @ekoermann and @kchonyc, we show that style can be discovered without supervision and controlled. 1/

i was diagnosed with thyroid cancer many years ago purely by chance, because i had to get blood work for my US green card application (thank you, USCIS!). i was in my mid-30’s and was reasonably healthy (or so i believed.) this was shocking and totally unpredictable news to me. thanks to the amazing team of clinicians at NYU Langone, i successfully went through a total thyroidectomy followed by radioactive iodine therapy. but, it was truly the most uncertain and confusing period of my life. this is when i first realized that no one can opt out of healthcare. being sick isn’t what you choose to or choose not to. it is something that unpredictably happens to all of us at some point for one reason or another. this is why it is a healthcare system that we collectively build and use to support each other at the society level. because it must support everyone, the complexity of creating, maintaining and improving this system is a Herculean effort that calls for all the help in the world. today, i am announcing @OrtetAI together with my dear co-founders, @keunwoochoi, @HenriDwyer, @elmanmansimov, @causalclaudia and Jeff, to lend our support to improving the health of each and every one of us. Ortet’s goal is to create a technological foundation that will enable health systems to deliver predictably better care to each and every patient. this will only be possible by working closely with all stakeholders in the broader ecosystem, which is enabled in part by Ortet’s close partnership with Thoreau. Ortet is taking the very first step of a long journey ahead, and at the end of this journey, i strongly believe we would be able to say that Ortet had contributed to building better, more predictable healthcare and thus to improving health of each and every one of us. see for more!

It is important to center the fact that Claude built on the approach that my colleague Lance developed, used tools that the field has developed, and (from what I have been told) used results in some of our recent papers. It’s a huge accomplishment, but should be framed as a combination of human and AI contributions. (To @AnthropicAI’s credit, I think the article does a pretty good job of this.) The fact that Claude can take a single people and figure out how to integrate the knowledge and use the tools as amazing, but it’s not coming out of the vacuum. This is an important opportunity for us to start to frame these developments, recognizing the human contributions and the power of these new tools. This is not an exemplar of the bitter lesson!

Quick break from jokes to share that I'm on leave from NYU this year and spending more of my time at Google, where I'm working to develop new ways to evaluate Gemini! I'm still based in NYC and checking in on my NYU group regularly to make sure their agents are not going rogue.

Welcome to CDS, Juan C. Perdomo! Perdomo joins CDS as Assistant Professor of Computer Science, Engineering, and Data Science. He researches performative prediction: what happens when a forecast changes the thing it predicts.

The point of a PhD is for the student to train to become an independent researcher. Part of this is coming up with their own research ideas, executed from start to finish. I don't see much value in massive projects with each person contributing little-they can do that in industry

wow young @W4ngatang from the pre-pandemic era! i personally enjoyed this paper by @kartik_goyal_ , @redpony and @BergKirkpatrick that gave a better motivated approach to sample from BERT.

globally there are roughly 30k phd students focusing on AI and adjacent areas. assuming half of 60k abstracts at iclr are placeholders due to neurips, it's roughly one a phd student. from this perspective .. not sure if we should be surprised.

A couple months ago I joined the AI x Economy Research team @Google to help lead the program. This is a critically important time to study how AI is transforming work, productivity, and economic activity. Excited to collaborate with an incredible crew doing foundational research.

it's not "out-of-control" at all. openai had all the control in the world (i.e. they could always literally turn off all their machines across all data centers.) they decided not to based on carefully calculated trade offs between finance-economy-reputation-customers-etc. just like any other co'a e.g. anthropic

@iskander @owl_posting @BenjaminGVincen loved it! i loved how you three covered everything from biology, medicine, trials, clinics and patients, and in doing so, touched upon wonders, limits and challenges. and, this reminded me that you started it more than a decade ago !