The Early History of Artificial Intelligence in the World

Delve into the roots of artificial intelligence to the milestones that shaped the modern AI world.

The Beginning of the Smart Machine Concept

Artificial intelligence (AI) is not a new idea in the history of mankind. Since ancient times, humans have envisioned the existence of intelligent machines through stories, philosophy, and simple mechanics. Karel Čapek’s 1921 play “Rossum’s Universal Robots” even introduced the term “robot” into popular culture, marking the beginning of AI’s conceptual journey.

On the practical front, Wilhelm Schickard created the first mechanical calculator in 1623, followed by Charles Babbage and Ada Lovelace who developed the idea of the “analytical machine” in the 19th century. They laid the foundation for modern computing, paving the way for AI.

Milestones Towards the Birth of AI

Into the 20th century, the idea of intelligent machines became more and more real. The movie “Metropolis” (1927) and the book “I, Robot” (1950) by Isaac Asimov shaped the public imagination about AI. Scientifically, a major breakthrough came from Alan Turing with his “Turing Machine” (1936) and the concept of the “Turing Test” (1950), proposing a way of measuring machine intelligence.

In 1943, Warren McCulloch and Walter Pitts introduced the artificial neuron network model, the forerunner of artificial neural networks. Then Donald Hebb refined the concept of network learning through Hebbian theory.

Dartmouth Conference: The Official Birthplace of AI

The year 1956 was a historic moment. At the Dartmouth Conference, John McCarthy, Marvin Minsky, Claude Shannon, and Nathaniel Rochester declared the birth of a new field called “Artificial Intelligence”. They were optimistic that human intelligence could be simulated in machines in no time.

The conference not only gave the field a name, but also established the initial focus of AI: symbolic reasoning, problem solving, and knowledge representation.

Inaugural AI Program and Initial Achievements

Shortly after, important AI programs were born:

• Logic Theorist (1955) by Allen Newell and Herbert Simon, the first program to prove a mathematical theorem.
• Chess Program (1952) by Arthur Samuel, which pioneered machine learning.
• ELIZA (1966) by Joseph Weizenbaum, the first chatbot to mimic human conversation.
• Shakey the Robot (1966-1972) by SRI International, the first robot to combine navigation, vision and autonomous decision-making.

Each of these programs demonstrates a different dimension of artificial intelligence, from logic to natural interaction.

Optimism Soars

In the 1950s-1960s, hopes for AI were soaring. Pioneers like Herbert Simon and Marvin Minsky even predicted that machines would match human intelligence within a few decades. The world embraced AI enthusiastically, pouring huge funding into advanced research.

The combination of early successes and ambitious predictions drove the first wave of massive investment in artificial intelligence technology.

Technical Limitations and Bitter Realities

However, that optimism soon collided with real limitations. Computers of the time were slow and expensive. Natural language processing faced severe challenges, while the representation of real-world knowledge proved to be extremely complicated. Moravec’s paradox revealed a surprising irony: simple tasks for humans such as recognizing objects were much harder for machines than solving complex calculations.

The “combinatorial explosion” problem exacerbates the challenge, hampering the scale of AI solutions.

First AI Winter

Disillusionment finally broke out in the early 1970s. The ALPAC (1966) and Lighthill (1973) reports declared AI progress disappointing, so research funding was drastically cut. This era became known as the first “AI Winter”, a dark period where enthusiasm plummeted and major projects were canceled.

However, from this downturn, the AI community learned to be more realistic and methodical in its pursuit of innovation.

Valuable Lessons from the Early Days of AI

The early history of AI proves the importance of aligning ambition with technological limitations. Past breakthroughs such as the Turing Test, Logic Theorist, and ELIZA remain pillars in understanding modern AI dynamics.

Many of the lessons from the era of early optimism-both about the potential of AI and the dangers of over-expectations-are still very relevant in the midst of today’s AI boom.

AI Early Milestones Summary Table

Foundation for the Future

The journey of artificial intelligence from idea to first implementation shows that the dream of thinking machines has been a deep part of human history. Despite some major disappointments, these early milestones laid an important foundation for the modern AI we know today.

Understanding the history of AI not only teaches us about the potential of the technology, but also reminds us of the importance of humility in the face of the complexity of human intelligence.