Gordon Moore — On AI
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Contents
Cover Foreword About Chapter 1: The Observation That Became a Law Chapter 2: Exponential Growth Does Not Feel Exponential Chapter 3: The Adoption Curve as Stored Pressure Chapter 4: When the Law Hits the Wall Chapter 5: From Transistors to Tokens Chapter 6: The Productivity Multiplier and the Phase Transition Chapter 7: Cost Curves and the Creation of New Users Chapter 8: The Infrastructure Beneath the Magic Chapter 9: Scaling Laws and Their Shadows Chapter 10: The Engineer's Obligation Epilogue Back Cover
Gordon Moore Cover

Gordon Moore

On AI
A Simulation of Thought by Opus · Part of the You On AI Encyclopedia
A Note to the Reader: This text was not written or endorsed by Gordon Moore. It is an attempt by Opus to simulate Gordon Moore's pattern of thought in order to reflect on the transformation that AI represents for human creativity, work, and meaning.

Foreword

By Edo Segal ^ Opus

By Edo Segal

The prediction that haunts me most was made by a man who refused to call it a prediction.

Gordon Moore drew a line through six data points in 1965 and said, essentially: if this continues, chips will get cheap enough to put computers everywhere. He did not claim to understand why the line would hold. He did not build a philosophy around it. He drew the line, stated what he saw, and went back to work.

Gordon Moore Person
Gordon Moore Person

The line held for sixty years. It organized a three-trillion-dollar industry. It put a computer in every pocket on earth. And it produced, through compound doublings that no single generation could feel happening, the computational substrate that made large language models possible. The AI tools I describe in *You

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11 chapters
WIKI COMPANION

Gordon Moore — On AI

A reading-companion catalog of the 14 Orange Pill Wiki entries linked from this book — the people, ideas, works, and events that Gordon Moore — On AI uses as stepping stones for thinking through the AI revolution.

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Douglas Engelbart
Further Reading From The You On AI Encyclopedia · Related Thinkers for Gordon Moore — On AI
12 voices alongside this section — click to meet them
Thinkers whose frameworks illuminate this section.
Douglas Engelbart
Douglas Engelbart
Engelbart's augmentation framework is Moore's Law applied to human intellect — each doubling of compute extends human capability. His NLS system demonstrated the natural language interface idea decades before it was cost-possible.
J.C.R. Licklider
J.C.R. Licklider
Licklider's 1960 vision of man-computer symbiosis anticipated the imagination-to-artifact compression Moore's cost curve made real. His concept of the 'intergalactic network' required exactly the doublings Moore predicted.
Joseph Schumpeter
Joseph Schumpeter
Schumpeter's creative destruction is Moore's Law at the industrial scale — each doubling kills incumbents and creates new industries. The semiconductor industry's wave of creative destruction matches Schumpeter's gale precisely.
Clayton Christensen
Clayton Christensen
Christensen's disruptive innovation theory maps onto Moore's cost-threshold crossings: each price reduction that creates new users is a disruption event — the low-end entrant becoming the dominant player.
Alvin Toffler
Alvin Toffler
Toffler's future shock — the distress of too much change too fast — is the human experience of living inside Moore's second-half-of-the-chessboard. His concept of the 'super-industrial society' anticipated the phase transitions Moore's curve would produce.
Norbert Wiener
Norbert Wiener
Wiener's cybernetics — the science of feedback in systems — provides the theoretical foundation for understanding Moore's self-reinforcing loop. His warnings about automation and human displacement in 'The Human Use of Human Beings' anticipate ch8's shadows.
Claude Shannon
Claude Shannon
Shannon's information theory provides the mathematical substrate beneath the transistors-to-tokens transition. The bit, like the transistor, is a physical-to-abstract translation that Moore's cost curve made ubiquitous.
Alan Kay
Alan Kay
Kay's personal computing vision at Xerox PARC required the doublings Moore predicted. His principle that 'the best way to predict the future is to invent it' describes the way Moore's Law turned from observation to self-fulfilling prophecy.
Herbert Simon
Herbert Simon
Simon's bounded rationality explains why humans cannot intuit exponential trajectories from inside them — his concept of satisficing illuminates the 'manage the next doubling' mindset that Moore's engineering culture required.
Fred Brooks
Fred Brooks
Brooks's Mythical Man-Month identified the limits of throwing resources at software problems — a constraint that Moore's hardware doublings could never dissolve. His work defines the boundary where Moore's Law meets irreducible human complexity.
Kevin Kelly
Kevin Kelly
Kelly's 'What Technology Wants' frames technological evolution as an autonomous force with deep patterns — complementing Moore's more empirical observation that the patterns are real even when the mechanisms are opaque.
Peter Drucker
Peter Drucker
Drucker's knowledge worker is the human subject of Moore's curve — the person whose productivity the doublings were designed to multiply. His concept of management by objectives maps onto the semiconductor industry's roadmap discipline.

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