Vision2077🏴‍☠️

A professor of engineering who failed math all through school built one of the most popular online courses in history by figuring out exactly why her brain had been working against her the whole time. Her name is Barbara Oakley, and she did not teach herself how to learn until she was in her mid-twenties, after leaving the military with a head full of Russian and almost no useful science knowledge. What she discovered about her own brain eventually became a Coursera course that over 4 million people have taken, and the core insight she teaches has been sitting in neuroscience research for decades waiting for someone to explain it in plain language. Here is the framework that changed how I think about every hard thing I am trying to learn. Your working memory is an octopus sitting in your prefrontal cortex with exactly four arms. Those four arms reach out and grab pieces of information, hold them in place, and manipulate them while you are actively thinking through a problem. Four is the limit. When you try to hold more than four things in conscious awareness at once, the arms start dropping things and everything becomes a scramble which is exactly what you experience as confusion when learning something genuinely difficult. This is not a flaw. It is a design feature. And the entire game of becoming expert at anything is learning how to game this constraint. The mechanism is something neuroscientists call chunking, and it is the most underexplained concept in all of learning. When you practice something enough times that it becomes automatic a guitar chord, a grammatical structure, a mathematical procedure, a debugging pattern in code your brain compresses it into a single neural package stored in long-term memory. That compressed package now fits in just one of your four working memory slots instead of filling all of them. Which means once you have built enough chunks, your octopus can reach down into long-term memory, pull up an entire complex procedure in a single grab, and still have three arms free to work with new information on top of it. This is what expertise actually is. Not raw intelligence. Not natural talent. A library of compressed patterns that can be retrieved quickly and stacked together to solve problems that would overwhelm a beginner whose working memory is still occupied with fundamentals. The finding that Oakley emphasizes most forcefully is the one that sounds backward until you understand the mechanism. People with smaller working memory capacity those who can only hold two or three items at once rather than four are often forced to develop stronger chunking habits earlier and more aggressively than people with larger working memories, because they have no choice. Their constraint becomes their training. Over time, that aggressive chunking practice can produce more robust expertise than a larger working memory that never had to be disciplined in the same way. The most powerful practical implication is this: when you feel completely overwhelmed trying to learn something, that feeling is almost always your four-slot octopus running out of arms. The solution is not to concentrate harder. The solution is to stop, isolate one small piece of the problem, practice it until it compresses into a single chunk, and only then pick up the next piece. You cannot learn everything at once because your brain was never designed to hold everything at once. It was designed to build libraries of compressed knowledge and retrieve them on demand. Every expert you have ever admired is not smarter than you. They just have a bigger library.

" Pete Hegseth, vous vous êtes saoulé dans un bar et vous avez commencé à hurler « mort à tous les musulmans », vous avez tenté d’abuser d’une stripteaseuse et ils ont dû vous sortir du bar. Ensuite, ils vous ont dénoncé pour abus sexuel et même votre propre mère vous a accusé de maltraitance envers les femmes.. " Tim Kaine, sénateur des États-Unis.

My heart rate just doubled

Elon Musk just diagnosed the smartest people in the room. Musk: “Most of the smart people I know actually don’t see a clear path… none of this is true.” Not a debate. A diagnosis. It cuts deeper than a wrong prediction. It exposes a failure of imagination dressed up as responsibility. Scarcity thinking wasn’t always wrong. For most of human history, inputs were fixed. Land was finite. Energy was scarce. Rationing made sense. That logic built the entire intellectual architecture of modern civilization. Population limits. Resource caps. Carbon budgets. Degrowth. Every single one shares the same buried assumption. The denominator never changes. It’s changing. Solar costs have collapsed 90% in a decade. Batteries are tracing the same curve. AI is compressing the cost of intelligence toward zero. Robotics is about to do the same to physical labor. These aren’t four separate trends. They’re one compounding loop. Cheap energy charges cheap batteries that power cheap robots guided by cheap intelligence. The cost of producing anything built from atoms and decisions is in freefall. When energy approaches zero cost, food scarcity becomes an engineering problem, not a physics problem. When intelligence approaches zero cost, medicine, education, and infrastructure stop being rationed by wealth. When robotics scales, human labor stops being the bottleneck between an idea and its execution. The ceiling on civilization doesn’t tighten. It dissolves. Musk: “You could support a civilization much bigger than Earth.” Not optimism. Arithmetic. The people demanding humanity shrink aren’t being careful. They’re running last century’s equations on this century’s variables. That’s not wisdom. That’s a category error with a trillion-dollar price tag. You don’t secure the future by rationing what exists. You secure it by compounding what’s possible. The math is already running. It doesn’t need their permission.