The Story of Artificial Intelligence
75 articles across 5 acts, tracing the complete intellectual journey of AI — through narratives, profiles, and pivotal events. 9 currently published. More every week.
Complete Series Overview
All 75 articles — published and planned — organized by act and track.
The Ancient Dream of Artificial Life
From the bronze giant Talos to Babbage's Analytical Engine — how ancient myths, medieval automata, and 19th‑century visionaries dreamed of artificial life long before the computer existed.
The Philosophers Who Asked 'Can Machines Think?'
Before the engineers came the philosophers. Leibniz dreamed of a calculus of thought. Pascal built the first mechanical calculator. Descartes asked whether mechanism had limits. The thinkers who laid the conceptual groundwork for everything that followed — and the questions they left unanswered that we are still wrestling with today.
The Dartmouth Conference, 1956: The Summer AI Was Born
In the summer of 1956, ten men gathered at a small New Hampshire college and gave a name to the dream of thinking machines. They were wildly overconfident, occasionally wrong, and completely right about the one thing that mattered most. This is the story of the week Artificial Intelligence was born.
The Logic Theorist, 1956: The First AI Program
On a winter night in 1955, a program running on a primitive computer proved a mathematical theorem for the first time in history. Its creators believed they had cracked the secret of human intelligence. They were wrong about that — but right about something more important. The full story of the Logic Theorist: the first AI program ever built.
The Turing Test, 1950: The Question That Still Has No Answer
In October 1950, a mathematician published a thirty-page paper in a philosophy journal that asked a deceptively simple question: can machines think? The paper proposed a test. The test sparked a debate. The debate has never ended. This is the story of the most important thought experiment in the history of AI.
Ada Lovelace: The First Programmer the World Forgot
She wrote the world's first computer program in 1843 — for a machine that didn't exist yet. Then history forgot her for a hundred years. The extraordinary life of Ada Lovelace, the woman who saw the future before anyone else.
Alan Turing: The Man Who Invented the Future
He broke the Nazi's unbreakable code, designed the architecture of the modern computer, asked whether machines could think, and was then chemically castrated by the government he had saved. The full, extraordinary, heartbreaking life of Alan Turing.
John von Neumann: The Man Who Designed the Modern Computer
He spoke eight languages, memorized entire books, and solved differential equations in his head for fun. He designed the architecture every computer in the world still uses today, helped build the atomic bomb, and died at fifty-three still dictating equations from his hospital bed. The astonishing, troubling, irreplaceable life of John von Neumann.
Clockwork Wonders: The Automata Era
Before computers, before electricity, before Ada Lovelace wrote the first program — craftsmen across Europe built mechanical marvels that walked, wrote, played music, and digested food. The extraordinary story of the automata era and the question it forced the world to ask.
The Birth of Neural Networks
How Warren McCulloch and Walter Pitts proved that simple artificial neurons could, in principle, compute anything — and why the world wasn't ready for the implications.
Cybernetics and the Dream of Control
Norbert Wiener's vision of a science of communication and control — in machines, animals, and society — that shaped the intellectual landscape of early AI.
Norbert Wiener: The Reluctant Prophet
A child prodigy who revolutionized mathematics, fathered cybernetics, and then spent his final years warning the world about the technology he had helped create.
The Perceptron, 1958
Frank Rosenblatt built a machine that could learn to recognize patterns — and ignited a debate about the nature of intelligence that has never fully resolved.
Frank Rosenblatt: The Man Who Built a Brain
The brilliant, charismatic psychologist who built the Perceptron — and whose reputation was destroyed by the very people who should have championed his work.
The First AI Winter
How overpromising, underdelivering, and a devastating book review brought the first golden age of artificial intelligence to an abrupt and bitter end.
Expert Systems and the Rise of Knowledge Engineering
How the AI field pivoted from general intelligence to specialized expertise — and built systems that actually worked in the real world.
MYCIN and the Medical AI Revolution
The expert system that could diagnose infectious diseases better than many doctors — and why it was never deployed in a hospital.
Edward Feigenbaum: The Father of Expert Systems
The Stanford professor who believed that AI's future lay not in general intelligence but in deep expertise — and proved it.
The Fifth Generation Project
Japan's audacious plan to leapfrog the world in AI — and why the rest of the world panicked, then lost interest.
Machine Learning Before Deep Learning
The forgotten algorithms — decision trees, Bayesian classifiers, support vector machines — that kept AI alive during the long years before neural networks returned.
Arthur Samuel: The Father of Machine Learning
The IBM engineer who coined the term "machine learning" and built a checkers-playing program that taught itself to win — in 1959.
The Lighthill Report, 1973
The British government report that cut AI funding to the bone — and gave the first AI winter an official stamp of approval.
The Second AI Winter
By the late 1980s, expert systems were failing, neural networks were ridiculed, and AI was a dirty word in academic circles. How the field survived.
Backpropagation: The Algorithm That Changed Everything
How a simple mathematical trick — rediscovered in the 1980s — gave neural networks the ability to learn, and set the stage for deep learning.
Geoffrey Hinton: The Godfather of Deep Learning
A family of distinguished scientists. A decades-long conviction that neural networks would work. And a Nobel Prize that vindicated a lifetime of stubbornness.
Yann LeCun: The Man Who Taught Computers to See
How a French researcher at Bell Labs built convolutional neural networks that could read handwriting — and why almost no one cared for twenty years.
Yoshua Bengio: The Theorist
The Montreal professor who built the theoretical foundations of deep learning while the rest of the field looked elsewhere.
ImageNet and the Convolutional Revolution
The 2012 competition that proved deep learning worked — and changed the trajectory of AI research overnight.
ImageNet 2012: The AlexNet Moment
A GPU-powered neural network crushed every competing approach — and deep learning went from academic backwater to dominant paradigm in a single weekend.
The GPU Revolution
How gaming hardware became the engine of the AI revolution — and why the most important technology in artificial intelligence was originally designed for rendering graphics.
Reinforcement Learning and the Game-Playing Bots
From TD-Gammon to AlphaGo — how AI learned to master games by playing against itself, millions of times.
Demis Hassabis: The Chess Champion
A child chess prodigy who grew up to build AlphaGo — and is now trying to build artificial general intelligence.
Transformers: The Architecture Behind the Revolution
The 2017 Google paper that introduced the Transformer — and changed natural language processing, and eventually everything else, forever.
"Attention Is All You Need", 2017
Eight Google researchers published a paper proposing a new architecture based on attention mechanisms. Within five years, it would reshape the entire field.
Ilya Sutskever: The Believer
From a student of Hinton's to the co-founder and chief scientist of OpenAI — the man who made GPT happen.
BERT, GPT, and the Language Model Wars
How two competing approaches to language modeling — bidirectional encoders and autoregressive decoders — set the stage for the LLM revolution.
Scaling Laws: Why Bigger Is Better
The discovery that neural network performance improves predictably with scale — more data, more compute, more parameters — and what it means for the future of AI.
Jared Kaplan and the Scaling Hypothesis
The theoretical physicist who helped prove that bigger neural networks are better — and what that means for the trajectory of AI.
RLHF: Teaching Machines What Humans Want
Reinforcement learning from human feedback — the technique that transformed raw language models into the chatbots we know today.
The Launch of ChatGPT, November 2022
A Tuesday morning product demo became the fastest-growing consumer application in history — and forced the world to reckon with AI.
Sam Altman: The Operator
The college dropout who became president of Y Combinator, then CEO of OpenAI — and the most influential figure in the most important technology of our time.
The OpenAI Board Crisis, 2023
Five days that shook Silicon Valley — and revealed the fault lines running through the most powerful AI company on earth.
The Race to AGI
How the concept of artificial general intelligence went from academic speculation to corporate goal — and what the race means for everyone else.
AI Safety: The Most Important Problem
The researchers trying to ensure that artificial intelligence remains beneficial — and why the problem may be harder than anyone thought.
Stuart Russell: The Cassandra
The UC Berkeley professor who has been warning about the dangers of superhuman AI since before it was fashionable — and whose warnings are now being taken seriously.
AI and the Future of Work
Which jobs will survive? Which will disappear? And what does the history of technological disruption tell us about what comes next?
AI in Medicine: The Promise and the Peril
From drug discovery to diagnostic imaging — how AI is transforming medicine, and the obstacles that remain.
AI and Creativity
Can machines create art? Can they write novels, compose symphonies, paint masterpieces? And if they can — does it matter?
The Alignment Problem
How do you build systems that do what you actually want — not just what you literally asked for? The hardest unsolved problem in AI.
3 Articles Per Week
New articles are published on a regular cadence: one Article, one Profile, and one Event per week, maintaining the three-track parallel structure throughout the series.
Rotation Pattern
Each act progresses through its articles in a structured rotation: Article → Event → Profile → Article → Article — ensuring narrative momentum while developing character portraits and documenting pivotal moments.
Where to Start
New readers can begin with A1: The Ancient Dream of Artificial Life — the first article in Act I — or jump to any act that interests you. Each article is self-contained, though reading in sequence provides the richest experience.