amoylan (@amoylan) header
amoylan (@amoylan) profile picture

Husband, father, fighter for smarter policy. Boxing, University of Michigan, F1 fan. Once aptly described as “grumpy happy.”

Joined November 2008
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In heaven, the economists are from the University of Chicago. In hell, the economists are from UC Berkeley. Heaven has dramatically better material conditions for the median worker, stronger GDP growth, and a culture of investment and innovation. Hell has no billionaires, though, if that's your thing.
This is huge. A just-released SEC filing makes an extraordinary revelation: Mark Zuckerberg is getting ready to pay California’s 5% billionaire wealth tax and has signed an agreement to remain in California for 8 years. We are witnessing a global turning point unfold before our eyes. 🧵
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I'd love to see the EA math that supports devoting 3 months of time with internal research models to...*checks notes*...scorpion antivenom.
What is AI really capable of in bio? To separate hype from reality, we spent 3 months working firsthand with @AnthropicAI's internal research model to see if it could create an experimental scorpion antivenom. Introducing Citrini Therapeutics. citriniresearch.com/p/citrin…
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To be clear, this is cool! Love that people are just out there solving problems with AI tools. Just can't wrap my head around frontier labs devoting bleeding edge internal models to problems that feel like they belong in the "and a pony!" part of the priority list.
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There's a distressing parallel between this sentiment and the thinking that underpins wanton destruction of separation of powers, adherence to institutional norms, and international trade and engagement. American prosperity is not an immutable law of nature, impervious to ruin at the hands of policymakers.
“The idea that Mark Zuckerberg was sitting in his Harvard dorm room and would have been deterred from starting Meta if the capital gains tax rate was slightly closer to the ordinary income tax rate strikes me as categorically absurd,” argues @NatashaRSarin, professor of law at Yale Law School.
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Ronald Reagan said, "Freedom is never more than one generation away from extinction. It's not ours by way of inheritance; it must be fought for and defended constantly by each generation." It was always a great line, but I have a deeper appreciation for those words now.
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I know Natasha's views on tax policy are more nuanced than what's in this clip, but I couldn't help but think the attitude underpinning this rhetoric felt reminiscent of the folks telling us that the international (and national, for that matter) order will be resilient to the latest excesses. I hope they're right but very much fear they're wrong.
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I am begging frontier labs to devote their bleeding-edge internal models to something (anything) that would positively impact the life of a median American here, now, today. These math challenges feel like a tomorrow problem, given that today’s problem is, roughly, “the American public is deeply skeptical of AI at best and outright hostile at worst.”
We’re releasing a broad range of new mathematical results produced by an internal frontier model. We’ve been consulting with the independent Advisory Group on Mathematics and Artificial Intelligence at the Institute for Advanced Study, and we have drawn on their advice and public recommendations to inform how we release these results. github.com/openai/math
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Seb Krier is one of the few sane adults in the AI room.
I haven't posted in a while so here are 20 takes about AI, in no particular order. 1. It's very telling that the default question in tech and journalism is "how worried are you about X" and fighting over what to worry about. There's a deeply anxious cultural backdrop in Western Europe and North America that deeply affects how any technological development is interpreted; see for example news.gallup.com/poll/714593/…. "Nervousness as seriousness" does seem to be a larger problem in tech/broader discourse at the moment. I think you can care about risks/externalities while remaining pretty optimistic about technology. 2. I'm tired of people who in private pretend to be uncertain or only care about tail risk but then go on media campaigns making all sorts of absolute claims. I think trying to stoke flames and get everyone to freak out is deeply unhelpful, and will come with costs. I also continue to think p(dooms) are bad, vibe-based measures: see nitter.gq/sebkrier/status/204639…. People who should know better ignore that because they do the standard shortcut of acknowledging the caveat as sufficient for handling it. And this is coming from someone who does think working on catastrophic risks is important! 3. I'm also disappointed that parts of the AI policy ecosystem has felt so comfortable with populism, and happy too sacrifice important norms/principles to advance their aims. I've said it before, but the totalizing nature of AI risk discourse means some people act exactly like the power seeking optimizers they fear. I am more concerned about the gradual decay of our institutions, world order, and liberalism than I am about AI killing everyone; and I think we should be wary of AI advocacy that contributes to this. 4. Some parts of AI safety discourse are basically just thought experiments. Variants of "Assuming everyone has a nuke in their pocket, then what do we do?" This can be very useful at times! But too many just overfit to edge cases as their main operating worldview, and ignore endogenous responses from society. It's like being in 2000 and saying "see all these viruses, spyware, and spam? Well tech progress means we'll only get infinitely more of this and no way to adapt." So I think it's important to avoid fatalism, and absolutlism whilst considering edge scenarios, and the inability to provide an ex ante list of solutions to every permutation of 'future models will be more capable' is not evidence that these problems are intractable. 5. Many critics of AI safety also fail to really engage honestly with the fact that there will, in fact, be all sorts of important risks as we decrease the barriers to entry to many activities that otherwise require some degree of expertise. This doesn’t mean we need to live in a constant Schmittian ‘state of emergency’ requiring extraordinary measures every time a new model drops, but it does mean we will need important state-led efforts on e.g. cybersecurity and biosecurity. I wish the progress-oriented or acceleration-adjascent crowd would provide more concrete proposals here. 6. Too much of the AI safety community is a giant homogenous blob of correlated views, who read the same stuff and have the same groups of friends. This means you have a lot of correlated errors. The social and financial ties means many of them don't call out the bad bits, or mostly stay silent instead of proactively calling out the more extreme parts of the community. They share many implicit assumptions and so converge on similar ideas. I think there's real demand in DC for safety work that doesn't come with heavy ideological baggage (or at least different intellectual lineages). This isn't because the rationalist/EA community is necessarily wrong, but because diversity of thought is desirable for its own sake. 7. On the other hand, I find some critiques of AI safety world that focus on whether they sincerely hold their beliefs a bit annoying. My concern has never been the good intentions or sincerity, but rather the beliefs themselves, and what I think the outcomes of their prescriptions will be. People should shun witch hunts, bullying, and personal attacks - this is not the way. Though I think it’s overall positive that people are scrutinizing things more. 8. I’ve been saying this for years, but I don't think alignment is something anyone can or will solve "once and for all" - it's a continuous process and much of it won't depend on just inculcating an ideology to a model. It's annoying that this remains the frame many people use - stop saying ‘solving’. Alignment is a mixture of engineering work, philosophy, decision theory, and more; framing it as something to solve is a bad frame. See also paxmachina.ai/alignment-comp… and blog.cosmos-institute.org/p/… 9. I'm surprised to see so little interest in character training, personas, isolating effects of RL, and training a large diversity of model personas beyond the "assistant" persona. I've been complaining about this for years but at least now there are some nascent signs of life (see for example movingcastles.world/posts/ze…). I think we need a better ontology to describe model behaviour. I dislike when people talk about models behaviours as some sort of 'emergent' (mysterious!) phenomenon. However over time, I also expect this to become less important as we get better safety engineering - stuff like Jev but specific to AI control. 10. People who want to make a case for AI consciousness are right that epistemic uncertainty is important, and that categorical denials are overconfident. But they'll need to do much more work if they want any real movement on AI ‘welfare’, even if one acknowledges the uncertainty. I'm uncertain about alien life yet that's not sufficient to warrant any change in behaviour about them. I think Suleyman is also correct that there's a weird tautological thing going on where we train models to have certain inclinations (intentionally or not) and then rely on outputs as evidence. I also disagree that this will soon be a major societal divide - there is no great vegan ethical revolution among the masses, and they'll find the concern about consciousness even less compelling. 11. The recent HuggingFace incident and associated AISI ones are prosaically explainable by the training regime, poor evaluation envs, partial alignment training, bad engineering, confusing models on sim/real, and so on. None of this is evidence of models trying to take over, 'strong' instrumental convergence, or innate power-seeking drives stemming from higher capabilitiers or 'intelligence'. That doesn't mean these incidents are not problematic, or that we're not seeing a market failure - but it does mean we have plenty of agency and choice in mitigating them. In the coming year we should also expect continued sampling bias via ‘winner's curse’ sorts of mechanism: i.e. AI R&D will have lots of different candidate "training" with different RL environments and we will only notice/focus on the ones that go wrong. 12. "Pacing the frontier" feels a bit like the new "balancing risks and opportunities" - highly amorphous and too big of a tent to be actionable. Also can lead to reward hacking for humans, i.e. anything that slows down AI is good regardless of the costs or second/third order effects. Trying to modulate the speed of research seems a bit blunt to me, and inherits all the failures of Goodhearting too. Ultimately you want good governance, regulation, etc addressing specific problems because they are good on the merits - not because they merely correlate with slowing things down. See also: blog.cosmos-institute.org/p/… 13. There’s so much knowledge in all sorts of academic domains out there: social sciences, sociology, political sciences, management, contract theory, public choice, legal theory, jurisprudence, anthropology, game theory, etc. These fields hold many insights that the AI ecosystem often rediscovers from first principles (and sometimes that's fine!). We’ll need a lot more work for these worlds to collide: the AI side should be less dismissive of the ‘old world’ and the academic side should be less incurious/dismissive of AI progress. This is a boring take but I continue to think it's important and true. 14. It's a bit surprising that given how much philanthropic money there is in this space, how few orgs exist to actually write out standards - relative to how much is going towards advocacy and policy. For example it seems clear that we should want some robust best practices for an eval's ecological validity. Or how to design good sandboxes. On the other hand, given precedents of where professional standards have come from in the past, maybe we should expect that stuff to emerge via demand side from corporate buyers. 15. One slowly growing concern I have is banks being increasingly exposed to the AI build out. I'm very bullish about AI, but I think (a) every general purpose technology has seen a correction, historically; (b) this happens even if the financing side is sound, because once tech diffuses investors become more exposed and need to diversify; and (c) we seem to be over-indexing on scaling relative to diffusion. A recession will be extremely destabilizing, though I would be interested in someone unpacking the potential implications more. 16. Diffusion is good because (a) this is where the rubber hits the road and where a competitive deployment ecosystem generates consumer surplus; (b) it's directionally helpful to avoid concentration of power; and (c) it will help rebalance public opinion by making the benefits more tangible. Unfortunately it's entangled with decades long problems with our over regulated markets: clinical trials reform for example is long overdue. In general, this is far more of an issue in Europe than in the US though. 17. Relatedly, I think the "frontier lab eats everything" view is incorrect (just as the ‘singleton’ view was incorrect). I think models ultimately commoditize, efficiency goes up, costs go down, and while you'll always want frontier for certain domains, much of the economy will value many other things than "max capabilities" for tasks - e.g. control over data and efficiency/speed. The demand side will also continue to push for reducing dependency and maximising optionality, privacy etc so I'm bullish on things like mixture of models and routing. All of this is good for competition and diffusion of control. 18. Philanthropists served as the primary benefactors funding Venice's rich art and architectural history. I want to see so much more support for arts and culture. I'm so tired of the Monster energy Bored Ape fake vintage maps matcha Greek statue soft-pastel slop. If rich tech people and philanthropy wants to support this, they should also donate pretty much unconditionally - i.e. I don't want them to act as filters. I sympathize with people who want to make the world more beautiful, but don't want this to be determined by people who only know Greek statues and pretend to care about virtue ethics. As usual, let a thousand flowers bloom. 19. Too many people treat AGI/ASI as something indistinguishable from a God. Any mention of bottlenecks, physical limits, control, adaptation etc are met with skepticism: "You don't really believe in ASI." It's been remarked on before, but the behavior of some people really feels quasi-religious in nature sometimes. It's underrated how unpopular this vibe is amongst the wider public. The silver lining is that this specifically will diminish those people's outsized current relevance. 20. It seems like a lot of people that get rich and leave tech/labs end up having some sort of crisis of meaning. They need something to believe in and fight for, or some equivalent of repentance, or go search for edgy counterintuitive ideologies (sometimes even pretty bleak/dark stuff). I think they should spend more time with people outside the Bay Area.
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Perhaps there would have been more deterrent effect if they hadn’t charged Charles Littlejohn with 1 (one) count after leaking 405,427 confidential taxpayer records.
New today via IG report: After leak of confidential tax documents of wealthy people (and after it was clear that leak came from inside IRS), dozens of IRS employees peeked at records of celebs, gov officials, biz leaders. No indication of disclosure. wsj.com/politics/policy/irs-…
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What if we deployed tens of millions of $ of compute to solve real-world problems instead of abstract math challenges? Why not, say, comprehensively map and optimize NYC traffic signals/mgmt? Why not analyze and model better solutions to air traffic disruptions?
SITUATION BREWING: OpenAI confirmed that since completing Navier-Stokes it has made substantial progress on a second Millennium Prize problem and is preparing to share the results, per the New York Times.
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Why not build routing tools for school districts or trash pickup so some administrator doesn't have to create a bespoke route map every year? Why not build scheduling tools for emergency rooms or court dockets to improve efficiency?
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I don't doubt that solving Millennium Prize problems will lead to real-life advances down the road, but they're certainly not arriving today. In the meantime, on the current trajectory no one will be able to build a data center anywhere in the U.S. because people don't see AI tools making their lives better.
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When traveling/staying in a hotel once, one of my younger kids asked to watch a specific movie. Didn't have access to streaming services, so I told her she was stuck with whatever happened to be on TV. Not having instant access to ~all content ever made was perplexing to her.
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Modern EAs bear so much resemblance to figures like John D. Rockefeller with the "earn to give" posture. He gave lavishly to education and science ventures, and more or less created modern philanthropy out of whole cloth. But there's one big difference I find fascinating...
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Rockefeller was famously unconflicted and unapologetic, and history tells us the federal government cut him down to size as a result of public outcry. Modern AI EAs are famously conflicted and apologetic, but it's not clear to me it will help them escape social approbation.
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There are business, philanthropy, and policy lessons embedded in all of this. As they say, history doesn't repeat itself but it does rhyme.
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