Monday, August 10, 2026

We Need To Talk About Leopold [& Situational Oblivion]

From the YouTube page:

Last week, 24-year-old Leopold Aschenbrenner — former FTX staffer, ex-OpenAI researcher, and author of the viral 165-page essay "Situational Awareness" — managed to lose roughly two-thirds of his $45 billion hedge fund in a matter of weeks. The margin calls arrived during his wedding weekend.

In this video I break down how a trader with no professional experience raised billions from Silicon Valley, why his AI "hedge" wasn't a hedge at all, and how leverage plus a concentrated bet on artificial intelligence stocks turned a great-looking expected return into a catastrophic outcome. Along the way we look at the cultural gap between Silicon Valley and Wall Street, why Ken Griffin's Citadel ended up buying the collapsing portfolio in an overnight fire sale, and the maths of volatility drag — the reason a high expected return can still drag an investor's typical outcome straight into the ground.

It's a story about leverage, risk management, expected versus median returns, and what happens when you go "full Kelly." Featuring reporting from the Wall Street Journal, The New York Times, Bloomberg, and the Financial Times, plus Victor Haghani's lessons from The Missing Billionaires.

I’ve listened to enough of Boyle’s stuff to have decided that he’s an absolute master of dry humor. But he really outdoes himself here. This one is so dry it could have sucked up all the rain that’s fallen on the East coast in the last several days.

Spain - Chick Corea | Rhythm Shaw & Purbayan Chatterjee

What does top-level achievement in literary criticism look like?

Recently Séb Krier asked:

What would a Fields medal type challenge look like in non-STEM domains? How should normative elements be evaluated? What would make me say “ok we have superinteligence in economics.”

I have no idea what a Fields medal type challenge would look like in literary criticism. But the main scholarly organization of literary critics in the United States is the Modern Language Association. They’ve given lifetime achievement awards since 1996. A got the list and uploaded it to Claude Opus 5 along with some remarks on what I knew about them and asked it for a short characterization of each. After going through the list it concluded with this remark:

One pattern you might find useful: the award splits fairly cleanly between theorists (Miller, Girard, Jameson, Spivak, Mitchell), field-founders who made a body of texts institutionally legible (Ruoff, Adorno, Saldívar, Gubar), and one editor-scholar of the old dispensation (Mack). Heilbrun sits across two of those. The chronology moves roughly from the third category through the first toward the second.

That makes sense to me. 

Getting back to Fields medals, I know little about them beyond the fact that they are awarded to mathematicians under 40. I don’t know to what extent the award is based on a body or word or some specific achievement, such as a spectacular proof (or two). If I were to compare Fields medalists with MLA lifetime achievers, it’s the theorists who are most comparable.

Here’s Claude’s commentary on the list:

A note on sourcing before the list: the MLA doesn't publish substantive citations for this award the way some societies do — the announcements are typically just "honors the lifetime scholarly achievement of a distinguished member." So your baseline assumption is right: it's a body-of-work award in every case. What follows is a characterization of the body of work being honored, not a paraphrase of an official rationale.

2025: Ramón Saldívar — A foundational figure in Chicano/a literary studies, best known for Chicano Narrative: The Dialectics of Difference (1990) and The Borderlands of Culture: Américo Paredes and the Transnational Imaginary (2006), which won the MLA Prize for the best book in US Latina/o and Chicana/o literary and cultural studies. He began as a comparatist — his first book was on figural language from Cervantes to Joyce — and his later work introduced the widely-discussed concept of a "postrace aesthetic" in contemporary ethnic fiction. He received the National Humanities Medal in 2011. (He's the brother of José David Saldívar, also a border studies scholar, which occasionally causes confusion.)

2023: W. J. T. Mitchell — Your association is correct and is probably the largest single factor: he is the Gaylord Donnelley Distinguished Service Professor at Chicago and edited Critical Inquiry for roughly four decades. Beyond the editorship, he essentially founded visual culture studies within literary departments — Iconology, Picture Theory, What Do Pictures Want? — arguing for the inseparability of word and image.

2020: Susan Gubar — Feminist criticism, yes, and specifically the Gilbert-and-Gubar collaboration: The Madwoman in the Attic (1979), No Man's Land, and The Norton Anthology of Literature by Women. At the award ceremony colleagues praised her not only for setting the standard in feminist criticism but for modeling collaboration itself as a mode of scholarly work. Her later cancer memoirs and Judas/Holocaust-related work extended her reach well beyond the academy.

2017: Gayatri Chakravorty Spivak — Both of your associations hold. The 1976 translation of Of Grammatology, with its long introduction, effectively brought Derrida into American literary studies; "Can the Subaltern Speak?" (1988) then made her central to postcolonial theory, alongside A Critique of Postcolonial Reason. She's also known for decades of rural literacy work in West Bengal, which she treats as continuous with the scholarship.

2014: Rolena Adorno — Colonial Spanish American literature, particularly the writings of the conquest and its indigenous counter-histories. She is Sterling Professor of Spanish at Yale, and produced a critical print and digital edition of Guaman Poma de Ayala's El primer nueva corónica y buen gobierno, serving as scholarly consultant to the Royal Library of Denmark, which holds the original manuscript. She's also written extensively on Cabeza de Vaca. Worth noting for your purposes: she was an early advocate for digital humanities, which is unusual in this list.

2011: Fredric Jameson — Body of work, as you say: Marxism and Form, The Political Unconscious, and Postmodernism, or, The Cultural Logic of Late Capitalism. I'd push back slightly on "no critical school" — he doesn't have a named method like Girard's, but "always historicize" and the postmodernism thesis have been programmatic for a lot of people.

2008: René Girard — Your characterization is right, and he's the outlier here in having a genuine school (Colloquium on Violence and Religion, Contagion, students and followers). Mimetic desire in Deceit, Desire, and the Novel (1961), the scapegoat mechanism in Violence and the Sacred (1972) and Things Hidden Since the Foundation of the World — a theory that outgrew literary criticism into anthropology and theology.

2005: J. Hillis Miller — Body of work spanning two distinct careers: the Geneva School phenomenological criticism of The Disappearance of God and Poets of Reality, then the Yale deconstruction of Fiction and Repetition, The Ethics of Reading, and Ariadne's Thread. He was MLA president in 1986, and his presidential address on "the triumph of theory" is a period document in its own right.

2002: A. LaVonne Brown Ruoff — She essentially built Native American literature as an academic field. She trained in nineteenth-century British Romanticism, but went to the Newberry Library to find primary sources when she began teaching, work that culminated in American Indian Literatures: An Introduction, Bibliographic Review and Selected Bibliography (MLA, 1990) — what Kenneth Roemer called the "bible" of the field. She also co-edited the MLA's Redefining American Literary History and did years of institutional work within the MLA on behalf of the field, which the award recognized as much as the scholarship.

1999: Carolyn HeilbrunToward a Recognition of Androgyny (1973) is right, but the book that traveled furthest is Writing a Woman's Life (1988), on the unavailability of narrative forms for women's biography. She was the first woman tenured in Columbia's English department, MLA president in 1984, and wrote the Kate Fansler detective novels as Amanda Cross. Her 1992 resignation from Columbia over the treatment of women there was itself a public event in the profession.

1996: Maynard Mack — Your hunch about editorial work is not just correct, it's arguably the whole story. He was an editor of the Twickenham Edition of Pope's poems, the standard edition, and edited the Twentieth Century Views series (143 volumes), Twentieth Century Interpretations (97 volumes), and New Century Views (17 volumes); he also served as general editor of the Norton Anthology of World Masterpieces. Alongside that he wrote King Lear in Our Time, The Garden and the City, and Alexander Pope: A Life, and taught at Yale for 45 years.

Red flowers on a street corner in Hoboken

Mongolian Girl Has a Laugh with her Camel.

Remarks by Billy Strings on the mind of a musician

David Marchese, The Interview: Billy Strings Escaped the Darkness. He’s Playing to Not Go Back. NYTimes, August 10, 2026.

Billy Strings has drawn from something old to do something entirely new. The singer and virtuoso guitarist, who is 33, has broken ground by using the elements of traditional bluegrass to become an arena-filling, chart-topping phenomenon, straddling the worlds of roots music and jam bands. Along the way he has also acquired a Deadhead-like legion of fans who follow his tours from concert to concert.

As improbable as it is that Strings can sell out cavernous venues across the country while playing bluegrass classics — in addition to his own introspective compositions, which he and his drummerless band often spin into long improvisations — it’s even more surprising when you know the path he took to get there. Strings, whose real name is William Apostol, was surrounded by poverty and drug addiction in his family growing up in small-town Michigan. Those demons have continued to haunt him: Strings’s mother died from a drug overdose last year at 64 years old. That loss inspired much of the music on his beautiful new album, “So Much for Goodbyes,” due out Aug. 28. He discussed the genesis of that album, among many other things, in our heart-wrenching conversation, which took place during a rare day off from his summer tour.

Well into the interview:

How does playing music help process the feelings that you have, whether it’s about your mom or anything else? It’s always been my coping mechanism, survival strategy and my medicine. Playing bluegrass music, it’s like a portal back to my childhood, back before I knew anything dirty about the earth. And it’s a way for me to go back to a time that was just beautiful and full of light, growing up playing music with my dad. And then songwriting is my cathartic and therapeutic way of dealing with things. I think sublimation is one of my main characteristics. Instead of letting this hard stuff drag me down, I try to make art from it, make lemonade, if you will.

A bit later:

When did you realize that you had a real gift for the guitar? That was early on. I started playing when I was about 4 years old. By the time I was 6 or 7, I could carry a tune, and I was my dad’s rhythm player. He would play all the lead and do all the fancy picking and singing, and I would hold down the rhythm. One of the biggest moments for me was I was sitting in my dad’s bedroom with him, as I would basically do every night, and he was teaching me the song “Beaumont Rag.” We would play the tune and I would mess up the second part every time. And I stopped us right in the middle of the song and said, “Why don’t you just play it and let me listen?” And so that’s what we did. Instead of trying to count, I listened to what he was playing. I listened to the melody. Then I was like, “All right, let me try it again,” and I nailed it. He was awful proud. He called my grandma, made her listen on the phone. That was a big moment for me. That’s when this listening thing started: I was able to listen to the music more intently and I could tell what chord was coming next. I used to think it was magic or something. I had no concept of music theory or anything. But my dad would play a G chord and then he would play a G seventh and my ear would just lead me. I’d be like, Well, the next chord’s probably going to be a C, and then it would be. It’s better to learn bluegrass and folk and hillbilly music that way than to try to learn from some academic point of view. It’s better to learn it on the back porch and to let it get under your skin, because then it’s not some equation, it’s a feeling. It comes from your soul.

Before shows:

I read an article about you that talked about how before shows, you used to get real anxious and have stomach pain. Is that still an issue? I definitely get nervous before a show. Sometimes moments before I’m walking onstage, I feel like I might pass out. I’ve just got to get into the first song or two, and halfway through the show I’m the complete opposite. I have all this energy. I feel great. I feel super confident, almost cocky even. There is that expectation from the crowd to do something amazing, and also that expectation from myself to always do better than I did the night before, because this is my livelihood and this is my life, and deep in the back of my mind, I’m scared that this is all going to go away, and maybe I’ll have to go back to the way life was when it was really hard. There’s this little devil on my shoulder that tells me I don’t deserve any of this, and thinks that I should be in some little trailer somewhere addicted to drugs, not a penny to my name. So it does feel like I’m playing for my survival a lot. Each time I walk onstage, I’m playing so that I don’t have to go back there.

Of course there is more at the link. 

Sunday, August 9, 2026

Construction in Hoboken

Séb Krier has 3 meta observations about the state of AI

Written out in full:

1. AI will continue to improve, get better integrated, and produce lots of value. This is true even if you think there's a bubble-y dynamic or an imminent correction. Lots of people genuinely believe the transformative prospects, but also lots of people have strong incentives to believe so AND for others to believe so too. So a lot of bulls are *honestly* bullish, whilst at the same time self-selecting into, and being driven by, discourse that happens to align well with their own interests.

2. Not exactly a revolutionary insight, but the very same facts will lead some people to think the exact opposite of what another group believes. The shape of recent progress will make some people think we are close to some sort of 'recursive self-improvement' dynamic (sometimes with unstated accompanying beliefs about speed of societal transformation). But another group, looking at the same results but indexing on other variables, will conclude we're seeing diminishing returns, jaggedness, and real but incremental progress (sometimes with unstated accompanying beliefs about the criticality of temporary failures).

3. A lot of public discussions on AI feel like they rest on a scaffold of leaky and highly imperfect abstractions. Too much is being written about models with reference to parables, metaphors, analogies, and stylized stories. Ofc this is somewhat unavoidable, but many jump to easy pattern matching and reason probabilistically *within* a particular causal story without adequately representing uncertainty over the story itself. There's so much noise that the correlations seem more explanatory than they actually are. Because the underlying understanding is itself so murky and uncertainty is uncomfortable, people go for easy familiar abstractions and are too quick to trust the data generating process itself. As a result of the above, the experts themselves are often more confused than one might expect, and so proper division of labour and deferral to authority is much harder in AI than in other established fields.

* * * * *

A comment from me: Also, much of the discourse about AI is based on concepts that arose before, say, the ChatGPT breakthrough to the public or the AlexNet breakthrough within the industry. It's discourse based on possibility not proved actuality.

Saturday, August 8, 2026

Mickey D's and out

AI in Africa

Paul Mozur, Adam Satariano, and Aaron Krolik, China’s A.I. Is Surging Across Africa. That Should Worry Silicon Valley. NYTimes, Aug. 5, 2026.

When Ernest Mwebaze, a tech developer in Uganda, was building an artificial intelligence system last year tailored for his country’s many languages, he tested American and Chinese tools to see which one could help.

China’s won.

The A.I. model from the Chinese internet giant Alibaba handled Uganda’s dozens of languages better than anything from Meta or Google, Mr. Mwebaze said. It was also inexpensive, and he could customize the model with his own data.

“We want to build things as cheap as possible, yet have them work really well,” said Mr. Mwebaze, a former research scientist at Google. His system, called Sunflower, is now used across Uganda, including by farmers to receive weather information and crop advice in local dialects.

Mr. Mwebaze, 47, is one of thousands of developers across Africa who have turned to Chinese A.I. models in the past year. In Kenya, entrepreneurs are using the models to streamline legal and business services. In Nigeria, they have made educational tools that teach high school students. In Ghana, developers are building local chatbots.

China’s A.I. is surging, especially in developing countries, as people look for the best possible system at the lowest possible cost. Unlike models made by the leading American A.I. companies OpenAI and Anthropic — which are closed and charge fees — the Chinese systems are publicly available to download and modify without payment or approval.

Chinese softpower:

Xi Jinping, China’s leader, is using A.I. as a form of soft power. At a July conference in Shanghai, he cast Chinese models as more reliable and cheaper and warned that A.I.’s benefits must be shared or they would create “new historical injustices.” Kenya, Ethiopia, South Africa and seven other African countries signed an A.I. pact with China at the event to promote international cooperation.

Chinese firms are also courting African developers with free computing and hands-on engineering help, developers said. Many Chinese-made smartphones in Africa come with Chinese A.I. tools preinstalled.

At the same time, China’s A.I. industry faces challenges. Companies have struggled to make money from their users and face security questions about data and links to Beijing. Many African developers still pay for American A.I. models, especially for technical tasks like coding.

Yet Africa’s experience shows the global A.I. competition is now a two-horse race.

China in Kenya's "Silicon Valley";

Konza Technopolis, a planned city, was announced 18 years ago as Kenya’s answer to Silicon Valley. Hopefully branded the Silicon Savannah, it is now a grid of empty boulevards and skeletal buildings, watched over by a powerful Chinese surveillance system.

It would look like a failed experiment but for one slate-gray building behind an electric fence. Financed by Chinese loans and built by Huawei, the site is a data center that runs computing for Kenya’s government.

For two decades, Chinese firms have wired Africa’s telecommunications networks and paved its roads. M-Pesa, Kenya’s celebrated mobile-money system, runs on Huawei technology.

These tech ties gave China a foothold in the continent, which it is using to sell A.I. One project advertised at Konza will use technology from the Chinese A.I. firm DeepSeek to combat telecom fraud.

Meanwhile, the American environment is risky:

In a Nairobi high-rise in June, a top Kenyan civil servant for technology said he was surprised when Anthropic pulled access to Fable, its powerful model, at the Trump administration’s behest.

It was a “wake up call” to the world, said John Tanui, the principal secretary in Kenya’s Ministry of Information, Communications and the Digital Economy. The abrupt move was a warning that relying on U.S. models could pose risks, he said.

Still, America remains in the game:

For all of China’s momentum, much of the A.I. money in Kenya still flows to U.S. companies.

Everyday users are on U.S. systems like ChatGPT and Claude. One 2025 survey found that 42 percent of Kenya’s 23 million internet users had used ChatGPT in the previous month, among the highest rate in the world.

Even Chinese models earn Americans money. Kenyan companies often run Chinese open-source models on cloud services from Amazon and Microsoft, so the U.S. giants make money from their data centers that deliver the technology to customers.

There's more at the link.

Note: I've been watching Africa ever since I learned that Nollywood was the 3rd largest film industry in the world by number of titles (after Hollywood and Bollywood). Africa pretty much leap-frogged over analog cinema direct to digital. Now, of course, they don't have to develop and manufacture the digital video equipment to produce films, they just have to use it. But they do have to service and maintain it. Things are a bit different with AI. But with Chinese open-weight models, who knows?

Norway has a museum dedicated to whales

Friday, August 7, 2026

François Chollet sees Large Reasoning Models (LRMs) in the future

What are large reasoning models?

Red flower

The expression of nuance and high dimensionality in LLMs

Jonathan Falk quoted over at Statistical Modeling, Causal Inference, and Social Science in a post by Andrew:

I have spent 50 years fighting the Curse of Dimensionality. I know this curse in my marrow. Brilliant inferences await me, but the space in which these insights are found is simply too vast to explore. So we simplify, reducing the dimensionality to something that while still vast, is confined to a hyperplane where we can, like Plato, see the projections of truth, not the truth itself.

But then what LLMs and their generation have taught me is that nuance, which is really just the inverse of inference (in that it’s the vast set of all things consistent with some inference) has an amazing boon of dimensionality. There appears to be no thought that can’t be described by a 14,000 dimension or so vector whose tuning has the huge advantage that 14,000-dimensional space is so empty that tiny nuances can be readily distinguished in such a space, so that you can hide uniqueness in the vastness of 14000-dimensional space that you couldn’t recover in a raw search in that same space.

Friday Fotos: Going to Mojo in Hoboken