00Overview 01Birth of AI 02Winters 03Deep Learning 04Transformers 05Explosion 06Epilogue Ecosystem
Chronological Index 001

A
(Brief)
History
of AI_

From Alan Turing's imitation game to autonomous agents — eight decades of machines learning to think, fail, and think again. A structured overview of artificial intelligence's defining moments.

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Key Figures
1950 Turing Test Computing Machinery & Intelligence
1956 AI Named Dartmouth Summer Workshop
AI Winters Funding collapses, 1974 & 1993
100M Users ChatGPT · fastest product ever
80+Years of ResearchFrom Turing (1950) to present
175BGPT-3 ParametersScale inflection point, 2020
$1BMicrosoft → OpenAIFirst major LLM investment
46+Active AI LabsPost-2022 proliferation
TURING PERCEPTRON EXPERT SYSTEMS DEEP BLUE IMAGENET ALPHAGO TRANSFORMER GPT-3 DALL·E STABLE DIFFUSION CHATGPT GEMINI CLAUDE LLAMA SORA CURSOR DEEPSEEK MIDJOURNEY TURING PERCEPTRON EXPERT SYSTEMS DEEP BLUE IMAGENET ALPHAGO TRANSFORMER GPT-3 DALL·E STABLE DIFFUSION CHATGPT GEMINI CLAUDE LLAMA SORA CURSOR DEEPSEEK MIDJOURNEY
01
Era One
1940s — 60sThe Birth
of AI
Laying the theoretical foundations of machine intelligence
Significance Index
Foundational
01 / 04
1950

The Turing Test

Alan Turing asks "Can Machines Think?" He proposes the Imitation Game — if a machine can fool a human, perhaps it thinks. The single most influential question in AI history.

02 / 04
1956

Dartmouth Conference

McCarthy, Minsky, Shannon & friends coin "Artificial Intelligence" at a summer workshop. The field is officially named. They estimate they'll crack it in one summer. Reader: they did not.

03 / 04
1958

The Perceptron

Frank Rosenblatt builds the first neural network hardware. The New York Times declares it will "walk, talk, see, write, reproduce itself and be conscious." Expectations were calibrated differently then.

04 / 04
1966

ELIZA — First Chatbot

Weizenbaum creates ELIZA at MIT — a program mimicking a therapist. Users form emotional attachments. Weizenbaum is horrified by their credulity. The AI therapist debate begins 60 years early.

Early computing
01 —Early Machines
Code
02 —The Code Era
Data
03 —Data & Logic
1956 — Dartmouth
The Field
is Named.
02
Era Two
1970s — 90sThe AI
Winters
Two cycles of hype, collapse, and institutional retreat
Significance Index
01 / 04
1969–74

First AI Winter

Minsky & Papert demonstrate perceptrons cannot learn XOR. Funding collapses. The UK Lighthill Report calls AI "disappointing." DARPA withdraws. The field enters hibernation.

02 / 04
1980

Expert Systems Boom

AI rebounds via rule-based Expert Systems encoding human domain knowledge. XCON saves DEC $40M per year. Lisp machines proliferate. Then the rules become impossible to maintain at scale.

Critical
03 / 04
1987–93

Second AI Winter

Expert systems fail to scale. Lisp machine market implodes. DARPA cuts funding again. Neural networks appear dead. The field shrinks to academic enclaves. Second full collapse in 20 years.

Milestone
04 / 04
1997

Deep Blue Defeats Kasparov

IBM's Deep Blue defeats world chess champion Kasparov 3.5–2.5. Kasparov alleges computational cheating. IBM retires Deep Blue immediately. The optics remain unresolved to this day.

93
"
We are on the edge of change comparable to the rise of human life on Earth.
Vernor Vinge, 1993 · Predicting the Technological Singularity
03
Era Three
2000s — 2010sDeep
Learning
GPUs unlock neural networks at scale — the modern era begins
Significance Index
01 / 04
2006

Hinton's Breakthrough

Geoffrey Hinton publishes "Learning Multiple Layers of Representation." Deep neural networks actually work. The AI community largely ignores it. The slow fuse is lit.

Inflection Point
02 / 04
2012

AlexNet — ImageNet

AlexNet surpasses ImageNet benchmarks by over 10 points. GPU acceleration meets deep learning. Every major lab pivots overnight. The modern era begins here.

03 / 04
2014

GANs — Generative AI Born

Goodfellow invents GANs at 2am after a debate. Two competing networks fight each other. Generative AI is born. Creative industries begin a long, complicated reckoning.

04 / 04
2016

AlphaGo — Go Defeated

DeepMind's AlphaGo defeats Lee Sedol 4-1 at Go — more board states than atoms in the observable universe. Sedol retires in 2019, citing the machine as undefeatable.

Neural networks
04 —Neural Networks
AI art
05 —AI Generates Art
Robot
06 —Thinking Machines
2017
Vaswani et al. — Google Brain
Attention Is
All You Need.
04
Era Four
2017 — 2022The
Transformer
One architecture reshapes the entire field — language, vision, reasoning
Significance Index
Architecture
01 / 04
2017

The Transformer Paper

Google Brain publishes "Attention Is All You Need" — eight authors, one paper. It replaces recurrent networks entirely. Every modern foundation model runs on this architecture.

02 / 04
2018

BERT & GPT-1

Google releases BERT; OpenAI ships GPT-1. Language models demonstrate genuine text comprehension. The scaling arms race begins — every point of compute translates to capability.

Scale Event
03 / 04
2020

GPT-3 — 175B Parameters

OpenAI scales to 175 billion parameters. GPT-3 writes essays, passes professional exams, generates working code. API waitlist exceeds one million developers. Microsoft invests $1 billion.

04 / 04
2021–22

Image Generation Emerges

DALL·E, Midjourney, and Stable Diffusion make text-to-image accessible at consumer scale. Generative media proliferates. Professional illustrators face an unprecedented market disruption.

05
Era Five
2022 — NowThe AI
Explosion
Consumer adoption, proliferation, and the emergence of autonomous agents
Significance Index
Consumer Inflection
01 / 04
Nov 2022

ChatGPT — Mass Adoption

OpenAI releases ChatGPT. One million users in five days. One hundred million in two months — the fastest consumer product adoption in recorded history. Google internally declares Code Red.

02 / 04
2023

Proliferation

Google launches Bard → Gemini. Meta open-sources LLaMA. Anthropic releases Claude. Mistral emerges from Paris. The landscape fragments rapidly across dozens of competing foundation models.

03 / 04
2024

Agents & Reasoning

The paradigm shifts from assistants to autonomous agents. Cursor writes code. Devin handles software engineering. OpenAI o1 implements chain-of-thought reasoning. DeepSeek demonstrates efficiency breakthroughs.

04 / 04
2025 —

Open Horizon

Multimodal. Autonomous agents. Drug discovery. Scientific reasoning. Physical robotics. The AGI debate intensifies. Whether or not general intelligence arrives this decade, the economic transformation is already underway.

AGI DebateRoboticsScientific AI
AI interface
07 —ChatGPT Era
AI future
08 —What's Next
Robots
09 —Age of Agents
06
Epilogue
2026 — 2035Where Do
We Go?
Probabilistic forecasts across two time horizons — near-term and decade-out
Certainty Index
Forecasting is probabilistic,
not certain.
Horizon 01 — Next 5 Years · 2026–2030
The Agentic Decade Begins
~85% Confidence
H1 / 01
2026–27

Agents Enter the Workforce

AI agents handle entire workflows — legal research, financial analysis, medical imaging, code review. White-collar disruption accelerates faster than policy can respond. The assistant era ends. The colleague era begins.

Agentic AIWorkforce DisplacementEnterprise
~80% Confidence
H1 / 02
2027–28

Multimodal Becomes Standard

Text, image, audio, video, and code collapse into unified models. AI that sees, hears, reads, and acts simultaneously becomes the baseline. The word "chatbot" is retired. Good riddance.

MultimodalFoundation ModelsUnified
H1 / 03
2028–29

Scientific Discovery Accelerates

AlphaFold showed the way. The next wave extends into drug design, materials science, climate modelling, and fundamental physics. Discoveries arrive that we weren't specifically looking for.

Drug DiscoveryClimate AIAlphaFold
H1 / 04
2028–30

Regulatory Frameworks Emerge

The EU AI Act is a beginning, not an end. Expect global divergence: EU tightens, US fragments by sector, China integrates AI into state infrastructure. An international body is proposed — and disputed.

EU AI ActRegulationGovernance
Horizon 02 — Next 10 Years · 2026–2035
The Shape of a New World
~55% Speculative
H2 / 01
2030–32

Physical AI — Robots in Context

Foundation models extend into physical embodiment. Robots navigate, manipulate, and reason in unstructured environments. Warehouses, hospitals, construction. Physical labour re-prices again.

RoboticsEmbodied AIPhysical Labour
~50% Speculative
H2 / 02
2031–33

Personalised AI — One Per Human

Every person carries a persistent AI companion trained on their life: communication style, medical history, professional knowledge. Memory and continuity become design challenges more than technical ones.

PersonalisationPersistent MemoryIdentity
H2 / 03
2032–35

AGI — The Contested Threshold

Whether a system reaches AGI depends entirely on definition. Narrow tasks: already surpassed. Common sense: rapidly closing. Flexible real-world agency at human level: the decade's open question.

AGIOpen QuestionDefinition Problem
H2 / 04
2033–35

The Unknown Unknowns

Every previous forecast missed the thing that actually happened. No one predicted GPT-3's emergent capabilities. No one predicted ChatGPT's adoption curve. The most significant development of the decade is probably not on any roadmap.

Black SwanEmergenceUnknown Unknowns
Confidence Key
80–90% High Confidence
60–80% Probable
40–60% Speculative
<40% Highly Uncertain
Probabilistic estimates only.
Entity Index
The AI Ecosystem
46 organisations · Click to visit