Artifact 1 · Four chapters · 70 years

The Story of
Artificial Intelligence

From a single question in 1950 to the tools you use every day — told in reverse.

Scroll
AI evolution — vintage mainframe flowing into a modern neural network brain

AI Is Everywhere

It writes your emails, recognizes your face, drives your recommendations, and generates images from a sentence. What once lived in research labs now lives in your pocket.

ChatGPT brought AI into everyday conversation. Copilot changed how developers write code. DALL-E turned text prompts into visual art. Voice assistants understand and speak in real time. The technology has become invisible — embedded in tools billions of people use daily.

AI timeline — four eras from vintage computer to neural network brain

The Breakthrough

AI stopped following instructions and started learning on its own. Deep learning cracked problems that hand-coded rules never could — and everything accelerated.

Before 2012, humans wrote the rules and AI followed them blindly. After AlexNet won ImageNet, the paradigm shifted: show the machine enough examples and it figures out the rules itself. Vision, speech, and language understanding all surged forward on the back of more data and faster GPUs.

AI evolution timeline illustration

The Rule-Following Era

For decades, AI could only do what engineers explicitly told it to. Decision trees followed rigid logic paths that couldn't adapt. Expert systems handled narrow domains like medical diagnosis but collapsed outside their training.

The hard ceiling was clear: hand-coded rules couldn't handle the real world's messiness and ambiguity. AI needed a fundamentally different approach — one that would take another 20 years to arrive.

AI evolution — from early computing to modern neural networks

Alan Turing
Asked a Question

In 1950, Turing published Computing Machinery and Intelligence and proposed something radical: what if machines could think?

"Can machines think?"

That one question launched the entire field.

One question → decades of rules → a breakthrough in learning → AI everywhere.

70 years of progress, one scroll.

About This Project

Introduction 70+ years of AI history as a scroll-driven narrative — accessible to any audience in under two minutes. Description Four-chapter visual timeline from Turing's 1950 question through the rule-based era, the 2012 deep learning breakthrough, and into today's generative AI landscape. Objective Make AI's evolution accessible and engaging for both technical and non-technical audiences. Process Researched key milestones, organized them into narrative chapters, designed scroll-driven visuals with reveal animations — built from scratch with HTML, CSS, and JavaScript. Tools HTML, CSS, JavaScript (IntersectionObserver), Google Fonts, ChatGPT for research. Value Synthesizes complex technical history into a clear narrative — a core skill for communicating AI concepts to non-technical stakeholders. Unique Value Tells the story in reverse — starting from what audiences already know (today's AI tools) and working backward to the origin, making history intuitive rather than academic. Relevance Understanding AI's origins informs decisions about its future — from model selection to infrastructure design. References Turing, A.M. (1950). "Computing Machinery and Intelligence." Krizhevsky et al. (2012). "ImageNet Classification with Deep CNNs." AIML-500, Indiana Wesleyan University.