A Short History of AI
The big idea: Artificial intelligence is not a sudden invention of the 2020s. It is a story of more than 70 years of bold dreams, painful disappointments, and surprising comebacks. The AI you use today — chatbots, photo filters, translation apps — stands on decades of earlier work. Understanding this history explains why AI works now when it failed so many times before.
By the end of this lesson you will be able to:
- Explain who Alan Turing was and what the Turing test (imitation game) checks.
- Say where and when the term "artificial intelligence" was born (Dartmouth, 1956).
- Describe symbolic AI and expert systems, and why they hit a wall.
- Explain the two AI winters and why the hype collapsed.
- Place the key milestones in order: Deep Blue (1997), ImageNet/AlexNet (2012), AlphaGo (2016), transformers (2017), ChatGPT (2022).
- Explain the "why now" formula: compute + data + algorithms.
The Whole Story on One Timeline
Before we dive into details, look at the whole journey at a glance. Notice the two cold "winter" periods when funding and excitement froze, and how the milestones come faster and faster after 2012.
The shaded blue bands are the two AI winters — periods when money and enthusiasm dried up. The orange dot (2012) marks the deep learning breakthrough that started the modern era.