Astral Codex Ten Podcast

The official audio version of Astral Codex Ten, with an archive of posts from Slate Star Codex. It's just me reading Scott Alexander's blog posts.

Apply For An ACX Grant (2025) 07/30/2025

Apply For An ACX Grant (2025) We’re running another ACX Grants round! If you already know what this is and just want to apply for a grant, use (should take 15 - 30 minutes), deadline August 15. If you already know what this is and want to help as a , , , , or , click the link for the relevant form, same deadline. Otherwise see below for more information. What is ACX Grants? ACX Grants is a microgrants program that helps fund ACX readers’ charitable or scientific projects. Click the links to see the and cohorts. The program is conducted in partnership with , a charity spinoff of Manifold Markets, who handle the administrative/infrastructure side of things. How much money is involved? I plan to contribute $200K. I expect (but cannot guarantee) an additional $800K from other donors, for a total of about $1 million. Most grants will probably be between $5,000 and $50,000, with a rare few up to $100,000. Depending on how much external donor interest there is, we will probably give between 10 and 50 grants. What’s the catch? There’s no catch, but this year we plan to experiment with replacing some grants with , and others with convertible grants. That means that if you’re a startup, we (ACX Grants as an nonprofit institution, not me personally) get some claim to future equity if you succeed. If you’re not a startup, you’ll sign an agreement saying that if your project ever becomes a startup, then we’ll get the equity claim. We’re still working on the exact details of this agreement, but we intend to have pretty standard terms and err in the favorable-to-you direction; obviously we’ll show you the final agreement before you sign anything. We’re doing this because some of our previous grantees became valuable companies, and it seems foolish to leave that money on the table when we could be capturing it and reinvesting it into future grants rounds. Please don’t let this affect your decision to apply. Our top priority remains charity, and we’ll continue to select grantees based on their philanthropic value and not on their likelihood of making us money. If you’re not a startup and don’t plan to become one, none of this should affect you. And if you have a good reason not to want to sign these agreements - including “I’m not savvy enough to know what this means and it makes me nervous” - then we’re happy to opt you out of them. What’s the timeline? We’d like to have grants awarded by October 1 and money in your hands by November 1. This is a goal, not a promise. What will the application process be like? You fill out a form that should take 15 - 30 minutes. If we have questions, an evaluator might email or call you, in a way that hopefully won’t take more than another 15 - 30 minutes of your time to answer. If you win a grant, Manifund will send you the money, probably by bank wire. Every few years, we might ask you to fill out another 15 - 30 minute form letting us know how your project is doing. What kind of projects might you fund? There are already lots of good charities that help people directly at scale, for example (which distributes malaria-preventing bed nets) and (which gives money directly to very poor people in Africa). These are hard to beat. We’re most interested in charities that pursue novel ways to change complex systems, either through technological breakthroughs, new social institutions, or targeted political change. Among the projects we’ve funded in the past were: Development of oxfendazole, a drug for treating parasitic worms in developing countries. A platform that lets people create prediction markets on topics of their choice A trip to Nigeria for college students researching lead poisoning prevention. A group of lawyers who sue factory farms under animal cruelty laws. Development of software that helps the FDA run better drug trials. A startup building anti-mosquito drones to fight tropical disease A guide for would-be parents on which IVF clinics have the highest successful rate of successful implantation. A university lab working on artificial kidneys You can read the full list and , and the most recent updates from each project . Is there anything good about winning an ACX Grant other than getting money? You’ll get my support, which is mostly useful in getting me to blog about your project. For example, I can put out updates or requests for help on Open Threads. I can also try to help connect you to people I know. Some people who won ACX Grants last year were able to leverage the attention to attract larger grantmakers or VCs. You can try to pitch me guest posts about your project. This could be a description of what you’re doing and why, or just a narrative about your experience and what you learned from it. Warning that I’m terrible to pitch guest posts to, I almost never go through with this, and I’m very nitpicky when I do. Still, you can try. We’re working on gathering a network of friendly professionals who agree to provide pro bono or heavily discounted support (eg legal, accounting, business advice, cloud compute) to ACX grantees. We’ve only just begun this process and it might not actually materialize. There are occasional virtual and physical meetups of ACX grantees; these don’t always result in Important Professional Connections, but are pretty interesting. What if I want those nonfinancial benefits for my project, but don’t need money? Apply for a grant of $1. But we’re pretty nervous about giving very-low-cost grants because it’s too easy to accept all of them and dilute our signaling value; for this reason, it might be harder to get a grant of $1 than a grant of $5,000, and we expect these to make up only 0 - 10% of our cohort. You might be better off coming up with some expansion of your project that takes $5,000 and applying for that. What are the tax implications of an ACX Grant? Consult your accountant, especially if you live outside the US. If you live inside the US, we think it’s ordinary taxable income. If you’re an individual, you’ll have to pay taxes on it at your usual tax rate. If you’re a 501(c), you’ll get your normal level of tax exemption. I want to fund you, how can I help? For bureaucratic reasons, we’re currently looking for donations mostly in the $5,000+ range. If that’s you, fill out the . If we’ve already talked about this over email, you don’t need to fill out the form, but we encourage you to do so anyway so we know more about your interests and needs. What’s the story behind why you have $200K to spend on grants every year, but are still asking for more funding? Some generous readers sent me crypto during the crypto boom, or advised me on buying crypto, or asked to purchase NFTs of my post for crypto. Some of the crypto went up. Then I reinvested it into AI stocks, and those went up too. I think of this as unearned money and want to give some of it back to the community, hence this grants program. I have a lot of it but not an unlimited amount. At the current rate, I can probably afford another ~5 ACX Grants rounds. When it runs out, I‘ll just be a normal person with normal amounts of money (Substack is great, but not great enough for me to afford this level of donation consistently). My hope is that I can keep making these medium-sized donations, other people can add more to the pot, and we’ll be able to drag this out at least five more rounds, after which point maybe we’ll come up with another plan. I’m a VC, how can I help? Some of our applicants are potentially-profitable startups, and we decide they’re a better match for VC funding than for our grants. If you’re willing to look these over and get in touch with any that seem interesting, fill out the . It will ask for more information on what kind of opportunities you’re interested in funding. I’m a philanthropist or work at a philanthropic foundation; how can I help? Some of our applicants are good projects, but not a good match for us, and we want to shop them around to other philanthropists and charities who might have different strengths or be able to work with larger amounts of money. If that’s you, please fill out the I’m good at evaluating grants, or an expert in some specific field; how can I help? If you have experience as a grantmaker or VC, or you’re an expert in some technical field, you might be able to help us evaluate proposals. Fill out the . By default we expect you’ll want us to send you one or two grants in your area of expertise, but if you want a challenge you can request more. If we’ve already talked about this over email, you don’t need to fill out the form, but we encourage you to do so anyway so I know more about your interests and needs. We expect to get more volunteers than we need, and most people who fill in the evaluator form won’t get contacted unless we need someone from their specific field. I’m a professional who wants to do pro bono work for cool charities, how can I help? Fill out the . If we get enough applicants, we’ll compile them into a directory for our grantees. I participated in the Impact Certificate Market last year, did you forget about me? Yes until Austin Chen reminded me last month No! Request final oracular funding by filling in the . Sorry, I forgot, where do I go to apply for a grant again? See . Please apply by 11:59 PM on August 15th. /episode/index/show/sscpodcast/id/37606730

Press Any Key For Bay Area House Party 07/23/2025

Your Review: Islamic Geometric Patterns In The Metropolitan Museum Of Art 07/22/2025

Book Review: Arguments About Aborigines 07/18/2025

Your Review: Of Mice, Mechanisms, and Dementia 07/15/2025

Your Review: Of Mice, Mechanisms, and Dementia [This is one of the finalists in the 2025 review contest, written by an ACX reader who will remain anonymous until after voting is done. I’ll be posting about one of these a week for several months. When you’ve read them all, I’ll ask you to vote for a favorite, so remember which ones you liked] “The scientific paper is a ‘’ that creates “a totally misleading narrative of the processes of thought that go into the making of scientific discoveries.” This critique comes not from a conspiracist on the margins of science, but from Nobel laureate Sir Peter Medawar. A brilliant experimentalist whose work on immune tolerance laid the foundation for modern organ transplantation, Sir Peter understood both the power and the limitations of scientific communication. Consider the familiar structure of a scientific paper: Introduction (background and hypothesis), Methods, Results, Discussion, Conclusion. This format implies that the work followed a clean, sequential progression: scientists identified a gap in knowledge, formulated a causal explanation, designed definitive experiments to fill the gap, evaluated compelling results, and most of the time, confirmed their hypothesis. Real lab work rarely follows such a clear path. Biological research is filled with what Medawar describes lovingly as “messing about”: false starts, starting in the middle, unexpected results, reformulated hypotheses, and intriguing accidental findings. The published paper ignores the mess in favour of the illusion of structure and discipline. It offers an ideal version of what might have happened rather than a confession of what did. The polish serves a purpose. It makes complex work accessible (at least if you work in the same or a similar field!). It allows researchers to build upon new findings. But the contrived omissions can also play upon even the most well-regarded scientist’s susceptibility to the seduction of story. As Christophe Bernard, Director of Research at the Institute of Systems Neuroscience (Marseilles, Fr.) , “when we are reading a paper, we tend to follow the reasoning and logic of the authors, and if the argumentation is nicely laid out, it is difficult to pause, take a step back, and try to get an overall picture.” Our minds travel the narrative path laid out for us, making it harder to spot potential flaws in logic or alternative interpretations of the data, and making conclusions feel far more definitive than they often are. Medawar’s framing is my compass when I do deep dives into major discoveries in translational neuroscience. I approach papers with a dual vision. First, what is actually presented? But second, and often more importantly, what is not shown? How was the work likely done in reality? What alternatives were tried but not reported? What assumptions guided the experimental design? What other interpretations might fit the data if the results are not as convincing or cohesive as argued? And what are the consequences for scientific progress? In the case of Alzheimer’s research, they appear to be stark: thirty years of prioritizing an incomplete model of the disease’s causes; billions of corporate, government, and foundation dollars spent pursuing a narrow path to drug development; the relative exclusion of alternative hypotheses from funding opportunities and attention; and little progress toward disease-modifying treatments or a cure. /episode/index/show/sscpodcast/id/37407650

Practically-A-Book Review: Byrnes on Trance 07/11/2025

Now I Really Won That AI Bet 07/11/2025

Now I Really Won That AI Bet In June 2022, I bet a commenter $100 that AI would master image compositionality by June 2025. DALL-E2 had just come out, showcasing the potential of AI art. But it couldn’t follow complex instructions; its images only matched the “vibe” of the prompt. For example, here were some of its attempts at “a red sphere on a blue cube, with a yellow pyramid on the right, all on top of a green table”. At the time, I wrote: I’m not going to make the mistake of saying these problems are inherent to AI art. My guess is a slightly better language model would solve most of them…for all I know, some of the larger image models have already fixed these issues. These are the sorts of problems I expect to go away with a few months of future research. Commenters objected that this was overly optimistic. AI was just a pattern-matching “stochastic parrot”. It would take a deep understanding of grammar to get a prompt exactly right, and that would require some entirely new paradigm beyond LLMs. : Why are you so confident in this? The inability of systems like DALL-E to understand semantics in ways requiring an actual internal world model strikes me as the very heart of the issue. We can also see this exact failure mode in the language models themselves. They only produce good results when the human asks for something vague with lots of room for interpretation, like poetry or fanciful stories without much internal logic or continuity. Not to toot my own horn, but two years ago you were naively saying we'd have GPT-like models scaled up several orders of magnitude (100T parameters) right about now (). I'm registering my prediction that you're being equally naive now. Truly solving this issue seems AI-complete to me. I'm willing to bet on this (ideas on operationalization welcome). So we ! All right. My proposed operationalization of this is that on June 1, 2025, if either if us can get access to the best image generating model at that time (I get to decide which), or convince someone else who has access to help us, we'll give it the following prompts: 1. A stained glass picture of a woman in a library with a raven on her shoulder with a key in its mouth 2. An oil painting of a man in a factory looking at a cat wearing a top hat 3. A digital art picture of a child riding a llama with a bell on its tail through a desert 4. A 3D render of an astronaut in space holding a fox wearing lipstick 5. Pixel art of a farmer in a cathedral holding a red basketball We generate 10 images for each prompt, just like DALL-E2 does. If at least one of the ten images has the scene correct in every particular on 3/5 prompts, I win, otherwise you do. Loser pays winner $100, and whatever the result is I announce it on the blog (probably an open thread). If we disagree, Gwern is the judge. Some image models of the time refused to draw humans, so we agreed that robots could stand in for humans in pictures that required them. In September 2022, I got some good results from Google Imagen and . Commenters yelled at me, saying that Imagen still hadn’t gotten them quite right and my victory declaration was premature. The argument blew up enough that Edwin Chen of Surge, an “RLHF and human LLM evaluation platform”, stepped in and asked his professional AI data labelling team. : the AI was bad and I was wrong. Rather than embarrass myself further, I agreed to wait out the full length of the bet and re-evaluate in June 2025. The bet is now over, and official judge Gwern . Before I gloat, let’s look at the images that got us here. /episode/index/show/sscpodcast/id/37370755

Your Review: School 07/11/2025

Highlights From The Comments On Missing Heritability 07/07/2025

Links For July 2025 07/07/2025

Contra Skolnick On Schizophrenia Microbes 07/07/2025

Your Review: Alpha School 07/04/2025

Your Review: Alpha School [This is one of the finalists in the 2025 review contest, written by an ACX reader who will remain anonymous until after voting is done. I’ll be posting about one of these a week for several months. When you’ve read them all, I’ll ask you to vote for a favorite, so remember which ones you liked] “Just as we don’t accept students using AI to write their essays, we will not accept districts using AI to supplant the critical role of teachers.” — Arthur Steinberg, American Federation of Teachers‑PA, reacting to Alpha’s cyber‑charter bid, January 2025 In January 2025, the charter school application of “”, a subsidiary of “”, lit up the education press: two hours of “AI‑powered” academics, 2.6x learning velocity, and zero teachers. Sympathetic reporters repeated the slogans; union leaders reached for pitchforks; Reddit muttered “.” More sophisticated critics dismissed the pitch as “selective data from expensive private schools”. But there is nowhere on the internet that provides a detailed, non-partisan, description of what the “2 hour learning” program actually is, let alone an objective third party analysis to back up its claims. 2-Hour Learning’s flagship school is the “Alpha School” in Austin Texas. The makes three claims: Love School Learn 2X in two-hours per day Learn Life Skills Only the second claim seems to be controversial, which may be exactly why that is the claim the Alpha PR team focuses on. That PR campaign makes three more sub-claims on what the two-hour, 2x learning really means: “Learn 2.6X faster.” (on average) “Only two hours of academics per day.” “Powered by AI (not teachers).” If all of this makes your inner Bayesian flinch, you’re in good company. After twenty‑odd years of watching shiny education fixes wobble and crash—KIPP, AltSchool, Summit Learning, One-laptop-per-child, No child left behind, MOOCs, Khan‑for‑Everything—you should be skeptical. Either Alpha is (a) another program for the affluent propped up by selection effects, or (b) a clever way to turn children into joyless speed‑reading calculators. Those were, more or less, the two critical camps that emerged when Alpha’s parent company was approved to launch the tuition‑free Arizona charter school this past January. Unfortunately, the public evidence base on whether this is “real” is thin in both directions. Alpha’s own material is glossy and elliptical; mainstream coverage either repeats Alpha’s talking points, or attacks the premise that kids should even be allowed to learn faster than their peers. Until Raj Chetty installs himself in the hallway with a clipboard counting MAP percentiles it is hard to get real information on what exactly Alpha is doing, whether it is actually working beyond selection effects, and if there is anyway it could scale in a way that all the other education initiatives seemed to fail to do. I first heard about Alpha in May 2024, and in the absence of randomized‑controlled clarity, I did what any moderately obsessive parent with three elementary-aged kids and an itch for data would do: I moved the family across the country to Austin for a year and ran the experiment myself (unfortunately, despite trying my best we never managed to have identical twins, so I stopped short of running a proper control group. My wife was less disappointed than I was). Since last autumn I’ve collected the sort of on‑the‑ground detail that doesn’t surface in press releases, or is available anywhere online: long chats with founders, curriculum leads, “guides” (not teachers), Brazilian Zoom coaches, sceptical parents, ecstatic parents, and the kids who live inside the Alpha dashboard – including my own. I hope this seven-part review can help share what the program actually is and that this review is more open minded than the critics, but is something that would never get past an Alpha public relations gatekeeper: /episode/index/show/sscpodcast/id/37281950

Missing Heritability: Much More Than You Wanted To Know 07/01/2025

Missing Heritability: Much More Than You Wanted To Know The Story So Far The mid-20th century was the golden age of nurture. Psychoanalysis, behaviorism, and the spirit of the ‘60s convinced most experts that parents, peers, and propaganda were the most important causes of adult personality. Starting in the 1970s, the pendulum swung the other way. Twin studies shocked the world by demonstrating that most behavioral traits - especially socially relevant traits like IQ - were substantially genetic. Typical estimates for adult IQ found it was about 60% genetic, 40% unpredictable, and barely related at all to parenting or family environment. By the early 2000s, genetic science reached a point where scientists could start pinpointing the particular genes behind any given trait. Early candidate gene studies, which hoped to find single genes with substantial contributions to IQ, depression, or crime, mostly failed. They were replaced with genome wide association studies, which accepted that most interesting traits were polygenic - controlled by hundreds or thousands of genes - and trawled the whole genome searching for variants that might explain 0.1% or even 0.01% of the pie. The goal shifted toward polygenic scores - algorithms that accepted thousands of genes as input and spit out predictions of IQ, heart disease risk, or some other outcome of interest. The failed candidate gene studies had sample sizes in the three or four digits. The new genome-wide studies needed five or six digits to even get started. It was prohibitively difficult for individual studies to gather so many subjects, genotype them, and test them for the outcome of interest, so work shifted to big centralized genome repositories - most of all the UK Biobank - and easy-to-measure traits. Among the easiest of all was educational attainment (EA), ie how far someone had gotten in school. Were they a high school dropout? A PhD? Somewhere in between? This correlated with all the spicy outcomes of interest people wanted to debate - IQ, wealth, social class - while being objective and easy to ask about on a survey. Twin studies suggested that IQ was about 60% genetic, and EA about 40%. This seemed to make sense at the time - how far someone gets in school depends partly on their intelligence, but partly on fuzzier social factors like class / culture / parenting. The first genome-wide studies and polygenic scores found enough genes to explain 2%pp of this 40% pie. The remaining 38%, which twin studies deemed genetic but where researchers couldn’t find the genes - became known as “the missing heritability” or “the heritability gap”. Scientists came up with two hypothesis for the gap, which have been dueling ever since: Maybe twin studies are wrong. Maybe there are genes we haven’t found yet For most of the 2010s, hypothesis 2 looked pretty good. Researchers gradually gathered bigger and bigger sample sizes, and found more and more of the missing heritability. A big 2018 study increased the predictive power of known genes from 2% to 10%. An even bigger 2022 study increased it to 14%, and current state of the art is around 17%. Seems like it was sample size after all! Once the samples get big enough we’ll reach 40% and finally close the gap, right? This post is the story of how that didn’t happen, of the people trying to rehabilitate the twin-studies-are-wrong hypothesis, and of the current status of the debate. Its most important influence/foil is , whose blog introduced me to the new anti-hereditarian movement and got me to research it further, but it’s also inspired by , (not himself an anti-hereditarian, but his research helped ignite interest in this area), and . (while I was working on this draft, the East Hunter Substack . Theirs is good and I recommend it, but I think this one adds enough that I’m publishing anyway) /episode/index/show/sscpodcast/id/37231270