A Chicago philosopher wrote one book in 1940 proving that 95% of the books you have read in your life, you didn't actually read, and Charlie Munger has been telling people to read it for 50 years.
His name was Mortimer Adler.
He spent 40 years at the University of Chicago, ran the editorial board of the Encyclopædia Britannica, and built his entire career on one uncomfortable observation about the people around him.
Most adults who called themselves well-read had not actually read a book in the real sense even once. They had run their eyes over the pages, registered the words, formed a vague impression, and put it back on the shelf.
The book had passed through them without ever entering them.
In 1940 he wrote How to Read a Book. It has stayed in print for 86 years.
Charlie Munger recommends it. Naval Ravikant recommends it. Fareed Zakaria recommends it.
Every serious thinker who builds a career on absorbing information eventually finds their way to this book, and the reason is that Adler had isolated something nobody else was naming clearly.
There are four levels of reading. Almost everyone is stuck on the second one. The fourth level is so different from what most people call reading that you have probably never done it in your entire life.
Level one is elementary.
You learn it as a child. You decode the letters into words and the words into sentences. You finish the sentence and understand roughly what it said. This is reading the way a 7-year-old reads, and almost every adult on earth has stopped developing past this point in some quiet way.
Level two is inspectional.
This is skimming. You move through a book quickly to figure out what it is broadly about. You read the back cover, scan the table of contents, glance at a few paragraphs, and form an opinion. Most adults who claim to have read 50 books a year are actually doing this. They are inspecting books, not reading them. They walk away with a vague sense of the argument and almost none of the evidence that supports it.
Level three is analytical.
This is the level Adler said most people have never properly experienced. You take one book and you wrestle with it for as long as it takes. You identify the question the author is trying to answer. You map their argument from front to back. You write your disagreements in the margins. You force yourself to articulate, in your own words, what the author is claiming and why. The point is not to finish the book. The point is to argue with it as if the author were sitting across the table from you. Most people never do this once in their life, because it is exhausting and slow and feels nothing like the reading they were taught as children.
Level four is the one almost nobody knows exists. Adler called it syntopical reading. The word means "across topics," and the technique is something closer to running a small private research lab in your own head.
You pick a single question that actually matters to you. How does power corrupt people. Why do civilizations collapse. What makes a marriage last. How does a person change their own mind. Then you assemble five or ten or twenty books from different authors, different centuries, different traditions, all of them taking a swing at the same question.
You do not read any of them cover to cover. You move between them. You find the chapter in book three that addresses the same question as the chapter in book seven. You force those two authors to argue with each other inside your own head.
The book stops being the unit of reading. The question becomes the unit. And the authors become voices in a conversation you are now hosting.
This is the level where reading stops being consumption and starts being construction.
You are no longer absorbing what someone else thinks. You are building a position of your own out of the friction between people who disagreed.
Adler argued that this is the only level of reading where you stop being a passive receiver of other people's ideas and start being someone who can produce ideas of their own.
The reason Charlie Munger has been recommending this book for 50 years is that this is exactly how Munger has always thought. He calls it building a latticework of mental models. The technique he is describing is just syntopical reading applied for a lifetime.
You take the strongest insight from psychology, the strongest insight from biology, the strongest insight from economics, and you stack them against the same problem until something new falls out the bottom.
The reason most people never reach level four is not that it is intellectually difficult. It is that it is logistically uncomfortable. It requires you to keep multiple books open at once.
It requires you to take notes that nobody is going to grade. It requires you to abandon the goal of finishing books and replace it with the goal of answering questions.
This is also why AI just changed everything Adler was teaching.
NotebookLM, Claude, and tools like them let you do syntopical reading at a speed that would have looked like magic to a Chicago philosopher in 1940.
You upload 10 books on the same question. You ask the AI to surface every place those authors agree and every place they contradict each other.
The technique Adler said almost nobody on earth had reached can now be run on a Sunday afternoon by anyone with a laptop and one good question.
The technique was always the unlock. The bottleneck used to be time. The bottleneck is now curiosity.
Most people will keep reading the way they always have. A book at a time. Eyes over the pages. No question driving it. No other authors in the room. Adler called that level two for a reason.
You are not behind on your reading list.
You are behind on the level you are reading at.
Let me trace the timeline here because nobody's connecting it.
Step 1: Scrape the entire internet. Every book, every article, every conversation, every piece of art, every forum post. Do it without asking. Do it without paying.
Step 2: Train a model on all of it. Call it "artificial intelligence."
Step 3: Go to BlackRock's Infrastructure Summit and announce: "We see a future where intelligence is a utility, like electricity or water, and people buy it from us on a meter."
Step 3 is where you sell people's own knowledge back to them. On a meter.
They took the collective output of human thought, compressed it into a model, and now they want to charge you by the token to access a version of what you and everyone you know already created.
One Reddit user put it perfectly: "They stole all this data from us, the people, our life's work, creativity, art, by devouring the internet and blowing through all copyright laws. Now they want to sell it back to us in the form of a utility."
Imagine if someone photocopied every book in the public library, burned the library down, and then opened a subscription service for the copies.
That's the metered intelligence business model.
And they're pitching it to infrastructure investors as though they invented water.
I strongly believe there are entire companies right now under heavy AI psychosis and its impossible to have rational conversations about it with them. I can't name any specific people because they include personal friends I deeply respect, but I worry about how this plays out.
I lived through the great MTBF vs MTTR (mean-time-between-failure vs. mean-time-to-recovery) reckoning of infrastructure during the transition to cloud and cloud automation. All those arguments are rearing their ugly heads again but now its... the whole software development industry (maybe the whole world, really).
It's frightening, because the psychosis folks operate under an almost absolute "MTTR is all you need" mentality: "its fine to ship bugs because the agents will fix them so quickly and at a scale humans can't do!" We learned in infrastructure that MTTR is great but you can't yeet resilient systems entirely.
The main issue is I don't even know how to bring this up to people I know personally, because bringing this topic up leads to immediately dismissals like "no no, it has full test coverage" or "bug reports are going down" or something, which just don't paint the whole picture.
We already learned this lesson once in infrastructure: you can automate yourself into a very resilient catastrophe machine. Systems can appear healthy by local metrics while globally becoming incomprehensible. Bug reports can go down while latent risk explodes. Test coverage can rise while semantic understanding falls. Changes happens so fast that nobody notices the underlying architecture decaying.
I worry.
Harvard Business Review research reveals that excessive interaction with AI is causing a specific type of mental exhaustion ( or "AI brain fry"), which is particularly hitting high performers who use AI to push past their normal limits.
A survey of 1,500 workers reveals that AI is intensifying workloads rather than reducing them, leading to a new form of mental fog.
While AI is generally supposed to lighten the load, it often forces users into constant task-switching and intense oversight that actually clutters the mind.
This mental static happens because you aren't just doing your job anymore; you are managing multiple digital agents and double-checking their work, which creates a massive cognitive burden.
The study found that 14% of full-time workers already feel this fog, with the highest impact seen in technical fields like software development, IT, and finance.
High oversight is the biggest culprit, as supervising multiple AI outputs leads to a 12% increase in mental fatigue and a 33% jump in decision fatigue.
This isn't just a personal health issue; it directly impacts companies because exhausted employees are 10% more likely to quit.
For massive firms worth many B, this decision paralysis can lead to millions of dollars in lost value due to poor choices or total inaction.
Essentially, we are working harder to manage our tools than we are to solve the actual problems they were meant to fix.
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hbr .org/2026/03/when-using-ai-leads-to-brain-fry
WATCH: Taiwanese grandmothers aged 89 and 91 train at the gym. An increasing number of elderly people in Taiwan’s super-aged society are hitting the gym to stay healthy, both physically and mentally.
Alan Turing took up long-distance running seriously after the war and nearly made the 1948 British Olympic marathon team (finished 5th at trials).
When asked why he trained so hard he said: "I have such a stressful job that the only way I can get it out of my mind is by running hard"
His marathon PR was 2:46:03
Imaginat si ets turista. Tinc uns amics taiwanesos que van venir a Barcelona per Setmana Santa per a un campus de futbol amb un grup de nens; els van robar i van haver de passar-se els dies a Madrid fent-se passaports nous en comptes de jugar a futbol.
Per als que es pregunten que faig a Taiwan.
A Catalunya fa massa temps que ens hem oblidat del que es viure sense por a que et robin, assetgin o coses tan simples com saber fer una cua.
Poder anar a una cafeteria, deixar el portàtil a la taula i marxar sense que passi res.
@Octogenarian_SH@protect_taiwan Precisely, the issue is that it's not just a piece of land. Taiwan has a very strong economy, currently the 7th largest stock market, and a mature democracy, ranked 12th globally. All signs of success in my dictionary.
Taiwan News:
In a sad development the government has announced that one of Taiwan’s most iconic sounds will pass into history this July as garbage trucks will stop playing Beethoven’s “Für Elise” due to copyright infringement.
At a press conference Taiwan Garbage Department 台灣垃圾署spokesperson Mr Yu Ren-jie 余仁傑 said “While Für Elise is in the public domain, it appears the specific arrangement of the classic we have been playing is copyrighted.”
He said the Dutch trademark agency Shietmark had contacted them and demanded royalty payments for use of the jingle. “While the Dutch graciously offered a low rate of 1 USD per day per garbage truck,” he said, “we have over 5,000 trucks across Taiwan, which would cost us NTD50 million per year.”
It turns out that a Dutch tourist by the name of Johann van der Smut had uploaded a clip of the yellow garbage truck playing the tune which brought this infraction to the attention of Shietmark. When contacted about this, Mr Van der Smut was apologetic. “My fahza loves Beethoven and I just wanted to bring a smile to his face,” he cried (at least that’s what we think he said).
Mr Yu said the government will hold a referendum in May to choose a replacement song but the public will only get to select from songs by Taiwanese artists to avoid possible future copyright issues. “Maybe a song by Jay Chow or GEM would get selected,” he suggested hopefully.
#Taiwan #Holland #Dutch #AustinPowers #AprilFools #aprilfoolsday2026 #Beethoven
Healthcare in Taiwan is phenomenal. I pay $30/mo for National Health Insurance. I’ve never waited over 10 min as a walk-in at this ENT clinic, which costs only $8/visit, and I always leave with a clear diagnosis and treatment.
I’m from the US. This is not normal but should be.
Don Knuth! Ok, starting to get surreal
“Shock! Shock! I learned yesterday that an open problem I’d been working on for several weeks had just been solved by Claude Opus 4.6 — Anthropic’s hybrid reasoning model that had been released three weeks earlier! It seems that I’ll have to revise my opinions about “generative AI” one of these days. What a joy it is to learn not only that my conjecture has a nice solution but also to celebrate this dramatic advance in automatic deduction and creative problem solving. I’ll try to tell the story briefly in this note.”
https://t.co/EcSXOzRqMW
The goal: a verified software stack, open source, mathematically guaranteed correct.
The role of the engineer changes but does not shrink. More design, more specification, more thinking. Less debugging, less hoping the tests are sufficient.
#LeanLang#LeanProver