Introduction
AI has become a buzzword in the last few years, but it’s been around for much longer!
Humans have had a long fascination with the creation of artificially intelligent beings, so much so that we can date the concept of AI all the way back to antiquity. But in this article, we’ll start when AI became a formal scientific discipline as we understand it today (so yes, we have to leave out Frankenstein’s monster).
While the groundwork began in the early 1900s, things really started happening from 1950 onwards.
Here is a look at how we got here.
Groundwork for AI: 1900- 1950
The term robots (or “artificial people”) was coined in a Czech play in 1921, reflecting the frenzy around the idea of artificial intelligence at the time.
Birth of AI: 1950- 1956
This is where AI officially enters the arena. Key milestones include:
- The coining of the term “Artificial Intelligence”
- The Turing Test: Introduced by Alan Turing (also known as the Imitation Game).
- Theseus: An electromechanical mouse created by Claude Shannon that could solve a maze without human interference.
- Logic Theorist: The first AI program ever created.
AI Maturation: 1957- 1979
The 1960s saw a burst of creation, while the 70s saw a struggle for funding for AI research leading to the first “AI Winter”. Despite this, significant innovations emerged:
- LISP: A programming language designed for list processing (still used today!)
- Machine Learning: The term itself was coined during this era.
- Eliza: Often cited as the first chatbot (originally called “chatterbot”).
- Deep Learning Foundations: Early neural network concepts were established.
- Unimate: The first industrial robot.
- The Stanford Cart: The first autonomous vehicle.
- Mark 1 Perceptron: The first supervised image classification learning system.
AI Boom: 1980- 1987
This period saw an increase in AI funding. Notably, the first Expert System, XCON (expert configurer), came into the commercial market, and Deep Learning techniques began to gain popularity.
AI Winter: 1987 – 1993
The Second Winter- Interest in AI dwindled across all sectors as high costs and low returns cooled enthusiasm again. Funding dried up, and progress slowed.
AI Agents: 1993- 2011
Despite lower funding levels, the early 90s didn’t disappoint in terms of AI research breakthroughs. This era brought AI into our homes (and games!):
- Deep Blue: The first AI system to beat a world champion chess player (developed by IBM).
- Kismet: The first robot simulating human emotions.
- Roomba: The first popular robotic vacuum cleaner.
- Siri: Apple’s virtual assistant, marking the rise of popular voice assistants.
- Commercial Adoption: Companies like Netflix and Twitter started using AI for UX algorithms and advertising in 2006.
- NASA Rovers: 2 rovers landed on Mars (Spirit & Opportunity), navigating the planet’s surface without human intervention.
Artificial General Intelligence: 2012 – present
This part is within recent memory. Most of us know the surge in the use of search engines, virtual assistants, and chatbots: Deep Learning transforms computer vision and NLP, chatbots evolve from simple scripts to sophisticated assistants, Generative AI (like DALL-E) changes creativity forever, and so on.
Conclusion:
The Takeaway? AI hasn’t changed overnight. It has been iterating, failing, freezing, and evolving for decades. Today, we aren’t witnessing a miracle; we’re witnessing maturity.
For students entering this field now: You aren’t starting from scratch. You’re standing on 100 years of shoulders. Use that context to build something meaningful.
In fact, you can start building today by availing a free 1:1 career consultation session or reach out to us on Whatsapp: