Nothing says “I have my cake and I’m eating it too” quite like detonating a functional marriage, upending your kids’ lives, and entering the post-35 dating market on the advice of multi-millionaire podcast hosts and actresses who face zero consequences for the toxic bile they spout. There is a special place in hell for the women who get obscenely rich telling other women the most catastrophically self-destructive advice imaginable under the guise of female empowerment.

People who cured / are curing their own cancer on X: 1/ @sytses - bone cancer, billionaire founder of Gitlab, developed 10+ personalized therapies for himself. 2/ @paul_conyngham - shrank his dog Rosie's mast cell cancer tumors after chemo and surgery weren't enough. Now backed by YC and Founders Fund 3/ @miriamgonp - stage 4 breast cancer, tumor sequenced, searching for vaccine manufacturer now 4/ @kevinace - stage 4 lung cancer, angel investor in 300+ companies, first drug stopped working after 18 months. Vaccine designed, now paying $300k out of pocket for the vaccine 5/ @masonbgrant: going founder mode on his his 32-year-old wife's rare liver cancer, sequencing her tumor with AI agents 6/ @ArunRLverma: former product leader at Atoms and Shopify, brain tumor, built a vaccine from his tumor. Now building an AI health agent startup based on what he went through We're going to make it

Countries are best summarized by their corporate income tax schedule description in the OECD tax database, a thread.

Paris, je t’aime!

J’ai entendu dire que la France était finie, qu’il était trop tard pour la sauver. Mais la France est toujours aussi belle, enviable même. Sa grandeur n’a pas disparu, elle ne demande qu’à renaître. Nous avons surmonté en un an un problème cent fois plus grave, sans avoir les moyens dont dispose la France. La France pourrait y arriver en une semaine.

The first gift is life. The second gift is good health. The third gift is to love and be loved. The fourth gift is peace of mind. The fifth gift is having the wisdom to know what to appreciate most. There are no other gifts that matter as much.

The mood has been a bit dour lately, so here are some less-obvious things that I expect to take shape over the next decade that I am excited about: 1. Space! Lots and lots of stuff is going to be happening in space by the mid-2030s, and right now the U.S. looks like it will be the leader by default, modulo the overhyped “race” to land a human on the moon again. Robots on the moon building and digging and cutting and adhering are more exciting than a person standing there taking pictures. The humans can come once the machines have built us habitats. 2. Increasing substitutability of hydrocarbons. This will lead to fewer supply chain disruptions and more stable, lower prices. This is a story about both supply elasticity and demand elasticity, and the geopolitical implications are underrated. Amazing for North America. 3. Private market exposure increasingly being an option for public investors, combined with Silicon Valley figuring how to use debt and other financial instruments more creatively than in the past. This seems like something America will be uniquely good at and I expect it to boost our already enviable lead in emerging technology capital allocation. 4. State and local government adoption of AI. This will vary widely by jurisdiction, but in at least some places you will see government administrative processes and public service provision have huge increases in efficiency. State and local government is where most of the American public services that people rely on are actually administered, so this is high-impact for people’s lives. 5. Advances in mathematics rapidly diffused to other fields. Historically it takes on the order of decades or centuries for discoveries from the bleeding edge of mathematics to be translated into practical applications, but I think AI will accelerate this dramatically. Lots of this will have the flavor of “small steps toward a much better world,” but it will accumulate. 6. Speaking of mathematics, lean! Lean is a programming language used by mathematicians to formally guarantee the truth of a proof. AIs can write lean and eventually they will be superhuman at it. This will have applications far beyond math, including cybersecurity and contract writing/negotiation/execution. 7. Fixing American’s shipbuilding problem by building boats instead. America has great boat-building capacity, but is awful at building ships. I want us to get better at building ships, but I am confident we can scale boat production. The Navy will soon have massive fleets of autonomous boats everywhere in the world. 8. New kinds of agriculture will become possible because of autonomy. Row-crop agriculture is heavily mechanized already, and automating the tractor, by itself, does less than you think for the economics of a farm. But with time, more labor-intensive crops will become economical. And vastly more diverse and complex crop arrangements will become possible too, which will be both ecologically, economically, and culinarily beneficial. The economics of agriculture could start to be kinder to small farms again. 9. Because of the previous item and advancements in biotechnology, logistics, and robotics, I expect that people are underrating how much healthier, more diverse, and flat-out better the American diet will be in 2035. 10. The subterranean will become an increasingly important field of human activity. New imaging sensors, including ones enhanced by an abundance of space-based imaging platforms, will make the subterranean more immediately legible. Better drilling and digging will become cheap and widely diffused. Among many other things, the opening up of the subterranean as an industrial frontier will change what we think of as a usable natural resource. 11. Greater variety and ornamentation in the physical world. Standardization is partially a function of scarce labor. Robotics can make beauty accessible again, if we choose to let it. There are many others, but I am out of time and space.

Ok two more: 1. AI will enable the design of custom enzymes that can catalyze industrial processes and chemical manufacturing faster than existing methods. In some cases this will make existing chemicals cheap enough that it becomes possible to use them for totally new use cases. Also, custom chemicals may enable the design of more efficient molecules to do things like separate rare earths from other elements, currently a very nasty process. 2. Computers will have superhuman smell. Sensors will be able to smell disease on people and crops. It will be possible to monitor industrial processes more effectively as well. Many strange implications here, but potentially exciting for biosecurity.

Intelligence must draw on memory. The mind must not simply compile data — as an algorithm now does more quickly than we can — but recall lived experiences, which contain depths of meaning that only the human soul can recognize, and connect more deeply with the goodness of these experiences. Everything that is good begins “with the Spirit” and thus possesses a breath, a dynamism and a sense of communion that, once experienced, are engraved upon the heart. vatican.va/content/leo-xiv/e…

tired of hearing men say they're afraid of wearing something cool bc they don't to stand out. good lord, grow a spine.

The point of man is to build, create, and improve the lives of others. The number on the screen is not relevant.

🇺🇸🇮🇳 U.S. Deputy Secretary of State Christopher Landau in the middle of New Delhi told Indians that India will not be allowed to develop to the point where it can compete with the US.

It would be fascinating to know where this rumor among non-mathematicians got started about the greatest living mathematician. Jean Pierre Serre is still alive. As is Edward Witten. And Simon Donaldson. As well as Peter Scholze. And Jacob Lurie. Not to mention Graeme Segal. Or Nigel Hitchin. Or Pierre Deligne. To say nothing of Dan Freed. Or Michael Hopkins. Or Maxim Konsevitch. Or ST Yau and Mikhail Gromov. Or Drinfeld and Beilinson. Or…. I think Terry Tao is amazing. I cannot shake the feeling that the New York Times and some people at Princeton came up with a meme that Tao won the prize as the greatest living mathematician. Which simply never happened. I’m sorry, but this is wrong. Nothing against Tao. But It’s just a meme.

RT @8teAPi: People clowning on him don’t understand what he’s saying. All the wealth of humanity to date supports perhaps 250k living mat…

DuckTales premiered 39 years ago today. I loved that show. Not for the gold. For the idea that adventure meant going somewhere wild with people you love. It was Indiana Jones for kids. Nobody's making the movie, so I made the trailer. Sound on. 🦆

Thank you Warren, for a lifetime of learning. @WarrenBuffett You have been a role model and a teacher like few others.

Walk down any residential lane in Japan, and you will spot a bright yellow sticker on ordinary front doors, doctor offices, and bakeries. It shows a cheerful cartoon snail or house: "Kodomo 110-ban no Ie" (Children’s Emergency Safety House). It is a quiet social contract between thousands of regular citizens: If a child walking home from school ever feels scared, gets lost, or encounters a suspicious stranger, they don't have to search for a police station. They can run up to any home bearing that yellow plate, knock on the door, and know they will be protected. The homeowner immediately opens the door, brings the child inside, gives them a glass of barley tea, and calls the police and parents. Zero government funding. Zero personal fame. Just everyday neighbors agreeing to act as human shields for other people’s children. An entire nation wrapped in an unbroken blanket of community love.

I love you

Simone Weil’s greatest insight was that attention is the foundation of morality and that letting your attention span degrade is the first step on the road to hell

A lot of people are missing Terence Tao’s point and thinking “mathematicians are upset that AI is better than them.” That’s not what he’s saying, and some people are forgetting that Tao is one of the most AI-pilled mathematicians out there. His point is that when people work on discovering something, along the way they invent new concepts. Those concepts later become useful far beyond the original goal, and enables further inventions. Finding a solution does matter, but the intermediate idea is often what makes the field richer, because other people can share it and build the next thing from it. In tech, we can use the analogy of collaborative software. We started with algorithms for merging changes in a Word document, and evolved that to concepts about versions, diffs, and merges, and later to real-time collaboration tools like Git, Google Docs, and Figma. Humans built upon these concepts and developed more powerful solutions. Terence’s worry is that a machine automating a solution robs the field of the value of developing the intermediate discoveries in the pursuit of larger discoveries. When automating a solution, the intermediate discoveries and invention of concepts can be buried or completely hidden in the black box. We don’t learn from them to build the next thing; it’s like we never made the invention of collaborative document editing and thus could not have the conceptual understanding to invent the next version – and since it’s hidden, we also don’t socialize them to allow other people to invent, too, a core tenet of collective discovery. So then, in both code and math, this leads to the atrophy of development of concepts in the field. In other words: pure ‘solution extraction’ that hides the process of discovery can leave the field with a checked-off theorem but little new insight or new questions to pursue. And it might prevent us from understanding a field deeper. I am seeing, first-hand, that atrophying of skills in software development. We push buttons and get solutions. There is much less incentive to develop new concepts and human skill. The bet most software companies are making is that LLMs are so effective in writing code that you’re still shipping overwhelmingly more value even with human skill atrophy, and it’s the right bet IMO. However, much of the software industry is built upon building things, not necessarily novel invention and research. In such an environment, you can say that you accept some atrophying of conceptual invention and human skill for more output. On the other hand, sectors like math and pure sciences that are focused on invention and insight might be the hardest hit by this. Practical/applied sciences might fall somewhere in the middle. An Alzheimer’s cure, room-temperature semiconductor, or highly effective carbon capture solution are far too valuable to sandbag and say only humans can do that to develop concepts in the ‘proper’ way. The outcome matters too much to treat the preservation of concept invention as the highest goal. Even there, though, hidden intermediates can slow the next breakthrough if nobody can see how the first one actually worked. So the question is not “is AI allowed to solve hard problems?” It is “in this field (math, science, tech, etc.), is the answer itself the main point, or are the concepts and abstractions we use to get there also the thing we need to maintain?”​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​ In pure math, there’s an argument that the intermediates are often more useful than the solution, and atrophy in concept development is highly detrimental to the field. Solving Navier–Stokes, contrary to what some people claim, has little practical application, and pure math might be one of those fields where just finding a solution isn’t the entire point, and can actually be contrary to the field, which is what Tao is worried about.