El país que más invierte en inteligencia artificial del planeta acaba de sancionar una ley nacional para obligar a sus ciudades a abrir bibliotecas y volver a los libros de papel. China era el candidato perfecto para enterrar el papel: pone más de cien mil millones de dólares al año en inteligencia artificial y es de los que más la incluyen en los currículos educativos. Si algún país iba a declarar que el libro ya no hace falta, que para eso está la máquina, era este. Sin embargo, hizo exactamente lo contrario: en vez de mandar todo a la pantalla, está promoviendo el libro por ley. Desde el primero de febrero, rige una norma que obliga a cada gobierno local a poner dinero en bibliotecas, abrir espacios de lectura hasta en las zonas rurales y sostener una Semana Nacional de la Lectura. Desde ahora, es obligación del Estado. ¿Por qué un país que ya tiene la mejor tecnología se molesta en legislar la lectura? Porque separaron para qué sirve cada cosa. La inteligencia artificial te sirve para producir, competir, ir rápido: es la herramienta. El libro te entrena en lo que ninguna máquina te da: atención sostenida y criterio propio. Es la cabeza la que después decide qué hacer con esa herramienta. Como lo resume uno de sus investigadores: solo a través de la lectura se llega a un pensamiento profundo e independiente. El premier Li Qiang lo decretó dentro del mismo plan quinquenal donde está su apuesta de inteligencia artificial. Las dos cosas son estratégicas y van de la mano. Mientras tanto, Estados Unidos hace el camino inverso: batió su récord de libros sacados de las escuelas (casi veintitrés mil desde 2021) y sus chicos sacaron las peores notas de lectura en más de veinte años, con cuatro de cada diez de cuarto grado que no llegan ni al nivel básico. La inteligencia artificial la va a tener todo el mundo. La cabeza para saber qué hacer con ella, no. Usala para pensar CON vos y no POR vos.

Pat Cash: “I was meant to play an exhibition match in Mallorca. 30 mins before, Becker says he can’t play. They tell me ‘you will play a 14 year-old’. I go on court, ready to give him a few games, so he won’t be upset. I lose 2-0, and ask him for his name: ‘Rafael Nadal.’” 🐐

The most thrilling hiking route in China

NeXTStep Release 3. Steve Jobs demonstrates it and sells it. I can only think of one founder today that has the guts to present their products, use their products, develop their products and test their products in public to this level.

Terence Tao has won every award mathematics can give a human being. Fields Medal. Breakthrough Prize. MacArthur Genius Grant. He is widely regarded as the greatest living mathematician. Not one of. The greatest. He just said something that should terrify every university on Earth. Tao: “We live in a particularly unpredictable era. I think things that we’ve taken for granted for centuries may not hold anymore.” Not years. Not decades. Centuries. The assumptions governing who gets to contribute to knowledge have been in place longer than most nations have existed. Tao just told you those assumptions are dissolving. Tao: “The way we do everything, not just mathematics, will change.” This is not a man who deals in hyperbole. He builds arguments the way he builds proofs. Piece by piece. Nothing unverified. When he says everything, he means everything. Tao: “In math, you previously had to basically go through years and years of education, be a math PhD before you could contribute to the frontier of math research.” That was the contract. You give a decade of your life to an institution. You grind through coursework, committees, dissertation reviews, postdoc rotations. Then maybe you get to touch the boundary of what’s known. The entire system was built on that bottleneck. Time was the gate. Credentials were the key. Tao: “Now it’s quite possible at the high school level that you could get involved in a math project and actually make a real contribution because of all these AI tools.” A high schooler. Contributing to frontier mathematics. The same frontier that used to require a decade of institutional obedience to even approach. He said this about math. He already told you this applies to everything. AI didn’t just speed up the path. It removed the path entirely. The university sold you a ten-year toll road. AI just paved around it overnight. The toll booth operators haven’t realized yet that no one’s coming. Tao: “In many ways, I would prefer the much more boring, quiet era where things are much the same as they were ten years ago, 20 years ago.” This is the line that should haunt you. The smartest mathematician on the planet would rather this wasn’t happening. He is not selling this. He is not positioning himself for a funding round. The acceleration is so violent that even the mind best equipped to process it would prefer it stopped. If Tao is uncomfortable, you should be paying very close attention to your own assumptions about what’s coming. Tao: “The things that you study, some of them may become obsolete or revolutionized, but some things will be retained.” That word “some” is doing enormous work in that sentence. It means the rest won’t be. Entire fields that people spent their careers building will collapse. Not slowly. Not politely. And Tao is telling you he can’t predict which ones survive. Tao: “You should be open to very, very different ways of doing science, some of which don’t exist yet.” Most people will scroll past this. It’s the most important line in the entire clip. He’s not saying learn new tools. He’s not saying adapt your workflow. He’s saying the methods themselves haven’t been invented yet. The frameworks don’t exist. You cannot prepare for what hasn’t been created. You can only build the kind of mind that doesn’t break when the ground shifts beneath it. Tao: “It’s a scary time, but also very exciting.” He said scary first. Every tech founder says exciting first and mentions risk as a footnote. Tao reversed it. When the most brilliant mind of a generation leads with fear and follows with possibility, that is not optimism. That is a man telling you the truth about what’s coming while still choosing to walk toward it. The people who survive the next decade won’t be the ones with the best credentials. They’ll be the ones who stopped mourning the world that was and started building for the one that doesn’t exist yet.

Misleading summary. Should be deleted. Altman doesn’t say a (known) new architecture is coming; he says he anticipates one will come someday. PS: I also think we need something radical and new. In fact that’s what I’ve been saying for the last decade. Excess focus on exploiting LLMs has likely delayed discovery.

💥25 Of the Most Famous Classical Music of All Time🌸🌸🌸 0:00 Handel - Hallelujah 0:33 J.S. Bach - Prelude no. 1 1:05 Franz - Hungatian Rhapsody no.2 1:42 Tchaikovsky - Waltz of the flowers 2:37 Beethoven - Moonlight sonata 2:59 Mozart - II Andante 3:47 Vivaldi IV - Winter 4:39 Schubert - No. 4, Ständchen 5:42 Camille - Dance Macabre 6:19 Ravel - Bolero 7:12 Franz - Ave Maria 7:49 J.S. Bach - Air 8:45 Brahms - Lullaby 9:40 Beethoven - Fur Elise 10:25 Mozart - Rondo alla turca 10:58 Puccini - O mio babbino caro 12:05 Johan Straus ll - The blue danube 12:55 Mozart - Lacrimosa 13:50 Debussy - Clair de lune 14:25 Beethoven - Ode to joy 15:02 Beethoven - Moonlight sonata I 15:46 Pachebel - Canon in D 16:39 Beethoven - Symphony no.5 17:05 Puccini - Nessun dorma 17:53 Chopin - Nocturne

Is Traditional Software Engineering Dead? “Does this mean that traditional software engineering is dead? Absolutely not. Software engineers—even the ones who are not necessarily tuning or training AI models—these are now among the most leveraged people on earth. Sure, the guys who are training and tuning models are even more leveraged because they’re building the tool set that software engineers are using. But software engineers still have two massive advantages on you. First, they think in code, so they actually know what’s going on underneath. And all abstractions are leaky. So when you have a computer programming for you—when you have Claude Code or equivalent programming for you—it’s going to make mistakes. It’s going to have bugs. It’s going to have suboptimal architecture. So it’s not going to be quite right. And someone who understands what’s going on underneath will be able to plug the leaks as they occur. So if you want to build a well-architected application, if you want to be able to even specify a well-architected application, if you want to be able to make it run at high performance, if you want it to do its best, if you want to catch the bugs early, then you’re going to want to have a software engineering background. The traditional software engineer is going to be able to use these tools much better. And there are still many kinds of problems in software engineering that are out of scope for these AI programs today. The easiest way to think about those is problems that are outside of their data distribution. For example, if they need to do a binary sort or reverse a linked list, they’ve seen countless examples of that, so they’re extremely good at it. But when you start getting out of their domain—where you have to write very high-performance code, when you’re running on architectures that are novel or brand new, when you’re actually creating new things or solving new problems, then you still need to get in there and hand code it. At least until either there are so many of those examples that new models can be trained on them, or until these models can sufficiently reason at even higher levels of abstraction and crack it on their own… And remember: there is no demand for average. The average app—nobody wants it, at least as long as it’s not filling some niche that is filled by a superior app. The app that is better will win essentially a hundred percent of the market. Maybe there’s some small percentage that will bleed off to the second-best app because it does some little niche feature better than the main app, or it’s cheaper, or something of the sort. But generally speaking, people only want the best of anything. So the bad news is there’s no point in being number two or number three—like in the famous Glengarry Glen Ross scene where Alec Baldwin says, “First place gets a Cadillac Eldorado, second place gets a set of steak knives, and third place you’re fired.” That’s absolutely true in these winner-take-all markets. That’s the bad news: You have to be the best at something if you want to win. However, the set of things you can be best at is infinite. You can always find some niche that is perfect for you, and you can be the best at that thing. This goes back to an old tweet of mine where I said, “Become the best in the world at what you do. Keep redefining what you do until this is true.” And I think that still applies in this age of AI.”

✨🇨🇳On the streets of Shanghai, China, a robot is walking a robotic dog.😂

难怪，有的风景死活找不到😅

«Teachers who make physics boring are criminals» — Walter Lewin

Everyone needs to hear this…

Wire management = art

Your company’s new “AI agent workflow” 🤣 That was painful to watch. 😭

Perfectionism vs. Consistency.

Everyone talks about Iranian oil in barrels. Nobody talks about what is inside them. That difference is why Western refineries have been running shadow networks through Dubai for twenty years to get it despite the sanctions. Crude oil is not a uniform commodity. It is a spectrum of hydrocarbons with different molecular weights, and the composition of a given crude determines how easily it converts into the products refineries actually want to sell: gasoline, diesel, jet fuel, heating oil. The measurement that captures this is API gravity. Higher API gravity means lighter crude with shorter carbon chains, which means lower energy cost to crack, lower processing cost to refine, and higher yield of the light distillates that carry premium pricing. Lower API gravity means heavier crude requiring more energy, more processing steps, more capital equipment, and producing a higher share of lower-value residuals. Iranian Light crude runs at 33 to 36 degrees API gravity with sulfur content between 1.36 and 1.5 percent. That is the refinery sweet spot. It is light enough to yield high fractions of gasoline and middle distillates without excessive processing costs, but heavy enough to produce the full range of products that complex refineries are designed to process. It is what petroleum engineers call an optimal blend crude. Now compare the alternatives. Venezuelan Merey heavy crude runs at approximately 16 degrees API gravity with sulfur between 3 and 5 percent. Refining it profitably requires a coking unit, a hydrocracker, and an extensive desulfurization train. The equipment exists. The economics work for refineries purpose-built around Venezuelan feedstock. It is not a substitute for Iranian crude. It is a different product requiring different industrial infrastructure. US West Texas Intermediate runs at 39 to 40 degrees API with sulfur below 0.25 percent. In theory, the cleanest and easiest crude to process. In practice, it is so light that it does not yield the heavier middle distillates a complex refinery needs to run at full capacity. European and Asian refineries built around medium crudes cannot switch to WTI without blending it with heavier crudes to achieve the molecular weight distribution their process units require. WTI is not a drop-in replacement for Iranian medium. Iranian oil fits where both US shale and Venezuelan heavy do not. It is the liquid that flows through the middle of the global refining system without requiring either the coking infrastructure for heavy crudes or the blending operations for ultra-light shale. That molecular fit is why it commands a persistent premium above comparable grades. It is why Indian refineries maintained Iranian crude purchases through every round of sanctions and negotiated the logistics to keep that flow moving. It is why the Dubai shadow banking and trading network that the UAE is now considering dismantling existed in the first place. The Strait of Hormuz does not just carry oil. It carries the specific category of oil that the global refining system was built to process most efficiently. Closing it does not just reduce supply. It removes the grade of crude that the system runs best on and forces every refinery in the world to run less efficiently on whatever it can find as a substitute. That is the premium embedded in the $82 oil price. Not just volume. Molecular weight. open.substack.com/pub/shanak…

A metaphor of why ups and downs are important in life.