The evolution of Artificial Intelligence: a beginner's timeline

Artificial intelligence (AI) is a term that dominates discussions today, from self-driving cars to chatbots and deep learning. But where did AI start? How did it evolve over the centuries? As a beginner exploring this fascinating field, I discovered the Artificial Intelligence Basics by Tom Taulli. This was included in my Learning Journey, and is available on O'Reilly.

1600s: the philosophical appearance

Before computers, philosophers pondered the nature of human intelligence and whether it could be replicated. René Descartes (1596-1650) introduced the idea of mind-body dualism, questioning if machines could ever “think.” Meanwhile, mathematician Gottfried Wilhelm Leibniz (1646-1716) dreamed of a logical language capable of solving problems mechanically.

1700s: imagining that automation is possible

This period saw the rise of mechanical automata, self-operating machines designed to mimic human behavior. One famous example is Jacques de Vaucanson’s mechanical duck (1739), which could flap its wings and even “digest” food. While not true AI, these creations demonstrated an early desire to replicate human-like intelligence and behavior in machines.

1800s: the foundation of computing

The 19th century laid the groundwork for AI with significant advances in mathematics and computing:

• Charles Babbage conceptualized the Analytical Engine, the first mechanical computer.
• Ada Lovelace, the world’s first programmer, foresaw that machines could go beyond simple calculations and create music or art (early vision of machine learning?)

1900-1950: the "birth" of AI concepts

With the rise of modern computing, the dream of intelligent machines started taking shape:

• Alan Turing developed the Turing Machine and later proposed the Turing Test (1950) to evaluate machine intelligence.
• Norbert Wiener laid the foundation for cybernetics, studying how systems regulate themselves

1950s-1970s: first AI boom

This period saw AI move from theory to practice:

• 1956: The Dartmouth Conference officially marked the birth of AI as a field of study.
• Early AI programs, like the Logic Theorist (1955) and ELIZA (1966), demonstrated problem-solving and natural language processing.
• However, AI faced setbacks due to limited computing power, leading to the first AI winter (1970s), when funding and enthusiasm declined.

1980s-1990s: AI Renaissance

Advances in machine learning and expert systems revived AI:

• Neural networks re-emerged, inspired by how the human brain processes information.
• IBM’s Deep Blue defeated chess champion Garry Kasparov in 1997, proving AI’s potential in complex decision-making.

2000s-today: AI in everyday life

The explosion of data and computing power propelled AI into the mainstream:

• 2010s: the rise of deep learning, enabled by powerful GPUs, led to breakthroughs in image recognition, self-driving cars, and AI-powered assistants like Siri and Alexa.
• 2016: Google’s AlphaGo defeated a human champion in the game of Go, a milestone in AI’s strategic reasoning capabilities.
• 2020s: AI models like ChatGPT and DALL·E demonstrated human-like text and image generation, raising questions about creativity and ethics.

The future of AI or what’s next

AI is advancing at an unprecedented pace, shaping industries from healthcare to finance and beyond. As we look ahead, ethical considerations, regulation, and AI’s societal impact will be key topics of discussion.