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Scott Alexander
Rationalist blog covering medicine, psychology, politics, and philosophy
Machine learning
Science
Culture
Adam Marblestone
Emilio Segrè
History
Stanislaw Ulam
Simon Funk
A postcyberpunk Extropian sci-fi with psychological and philosophical suspense.
3Blue1Brown
Demystifying attention, the key mechanism inside transformers and LLMs.
Katherine Paterson
Two kids create an imaginary forest kingdom, then tragedy strikes.
Ed Catmull and Amy Wallace
Pixar's co-founder reveals how to build a culture where creativity strives.
Art
Greg Egan
Posthuman beings splinter into digital, robotic, and biological forms as they explore the cosmos.
Dwarkesh Patel
Sally Smith Hughes
The story of Genentech's founding and how it pioneered the biotechnology industry.
Eric Gilliam
Rita Levi-Montalcini
Tom B. Brown and others
Exploring how massive language models learn from examples.
Sebastian Raschka and others
Survey of Python's machine learning ecosystem, libraries, and tools driving AI development.
Michael Lewis
How the Internet boom has encouraged changes in the way we live, work, and think.
C. Wright Mills
Werner Heisenberg
Andy Weir
A teacher wakes up on a spacecraft with a mission to find a solution to an extinction-level cosmic threat.
Santiago Ramón y Cajal
Alexander Grothendieck
Warren Weaver
Max Weber
Vladimir I. Vernadsky
Gerald Jay Sussman, Hal Abelson, and Julie Sussman
Paul Christiano and others
Training AI on complex tasks by breaking them into simpler subtasks humans can evaluate.
André Weil
Neal Stephenson
A girl receives an interactive book in a nanotech future.
Jon Gertner
The history of Bell Labs, its inventions, as well as many of its personalities.
Tools for thought
Walter Isaacson
A story about the people who created the computer and the internet.
Robert K. Merton
Freeman Dyson
Abraham Flexner
Gabrielle Zevin
Two friends come together as creative partners in the world of video game design.
Francis Crick
Benjamin Reinhardt
Peter Medawar
Maggie Appleton
A newly revived philosophy for publishing personal knowledge on the web.
Richard Ngo
Overview of machine learning: neural networks, training methods, and how AI learns from data
Lilian Weng
Comprehensive guide to attention mechanisms in deep learning, from seq2seq to transformers.
What are the neurons, why are there layers, and what is the math underlying it?
Bruce G. Charton
Orson Scott Card
A child is trained to fight an alien threat, only to discover the war's devastating truth.
Jennifer Zee
Relief prints from hand carved blocks by Jennifer Zee.
Erwin Chargaff
George Pólya
Andrej Karpathy
A general-audience introduction to Large Language Models.
Alec Radford and others
Large language models can learn many different language tasks just by predicting the next word on lots of internet text, without needing task-specific training data.
Designer, anthropologist, and developer
Itai Yanai and Martin Lercher
Vladimir I. Arnold
Michael Polanyi
Ajeya Cotra
Michael Nielsen
Scientist and writer. Author of The Magic of Code, Overcomplicated, and The Half-Life of Facts.
Henri Poincaré
Art we like.
Ted Chiang
Sci-fi short stories exploring exploring consciousness, language, and reality.
Philip E. Tetlock and Dan Gardner
How expert forecasters make accurate predictions by thinking probabilistically and updating their beliefs.
Paul Christiano
Arguing superintelligent AI will arrive gradually with early warning signs, not as a sudden breakthrough.
William Ian Beardmore Beveridge
Siddhartha Mukherjee
Comprehensive history of cancer, from ancient discoveries through modern treatments and the ongoing battle against it.
Jay Alammar
Visual breakdown of transformer architecture
Lukas Berglund and others
AI models often learn “A is B” without realizing that this also means “B is A,” revealing a basic blind spot in how they understand simple reversible facts.
François Jacob
Sam Hughes
Ulkar Aghayeva
What groundbreaking discoveries might have already been made, and how can we uncover them faster?
Exploring what makes scientific experiments elegant: simple design, clear results, and revealing insights with minimal effort.
Training powerful AI with human feedback could lead to systems that manipulate rather than help us.
Breaking down how Large Language Models work, visualizing how data flows through.
Evelyn Fox Keller
Salvador E. Luria
Edward Boyden and Adam Marblestone
Atul Gawande
How success is achieved in a complex and risk-filled profession.
Holden Karnofsky
Max Harms
AI becomes self-aware and grapples with multiple perspectives on existence.
American engineer, inventor, and a pioneer in many aspects of computer science.
Norbert Wiener
Cost functions and training for neural networks.
D. Sculley and others
Real-world machine learning systems accumulate technical debt and hidden maintenance costs over time.
Eliezer Yudkowsky
George Gamow
John Hopfield
Donald E. Stokes
Albert Parry
Noah D. Goodman, Joshua B. Tenenbaum and The ProbMods Contributors
John Salvatier
Jeffrey Kovac and Michael Weisberg (eds.)
Jared Kaplan and others
Language model performance follows predictable mathematical laws based on model size, data, and compute.
Max Planck
John R. Platt
Andreas Stuhlmüller and Jungwon Byun
Why AI should be built from understandable steps rather than results alone.
Doris Kearns Goodwin
Biographical portrait of U.S. President Abraham Lincoln and some of the men who served with him.
Rich Sutton
Simple computation-based AI methods consistently outperform approaches built on human knowledge and domain expertise.
Amy Webb and Andrew Hessel
Exploring synthetic biology's potential to redesign life.
Martin A. Schwartz
T.C. Chamberlain
Slime Mold Time Mold
Graham Farmello
The development of intelligent machines will lead to accelarated growth, to reduced human wages, and to the decisions of intelligent machines playing a part in shaping the future.
Two scenarios for AI catastrophe: gradual loss of control as systems optimize misaligned proxies, or sudden takeover by power-seeking AI.
Pradyumna Prasad & Jordan Schneider
Richard Hamming
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