Although the idea of machines thinking like humans sounds futuristic, the journey of artificial intelligence, or AI, began many years ago. Long before computers existed, ancient stories told of artificial beings doing human tasks. These myths hinted at a dream to create smart machines.
Fast forward to the 1940s, when Alan Turing, a brilliant mathematician, worked on cracking secret codes during World War II. His efforts helped lay the groundwork for AI. In 1950, Turing suggested computers could learn to think like humans. He even created the Turing Test to check if a machine could act intelligently.
By the mid-20th century, AI started taking shape as a real idea. In 1956, John McCarthy named it “artificial intelligence” at a meeting at Dartmouth College. This Dartmouth Conference became the birthplace of AI as a field of study. That same year, Allen Newell and Herbert Simon built the Logical Theorist, the first AI program. Notably, this event sparked widespread excitement and set the stage for future advancements (Dartmouth Conference excitement).
In 1956, John McCarthy coined “artificial intelligence” at Dartmouth College, marking the birth of AI as a field of study.
A few years earlier, in 1951, Marvin Minsky and Dean Edmonds made the first artificial neural network called SNARC. These early steps showed machines could mimic some human thinking. In 2012, the development of AlexNet for image recognition marked a significant leap forward in AI’s ability to process visual data.
In the late 1950s, Frank Rosenblatt invented the Perceptron, another type of neural network. Soon after, in the 1960s, rule-based systems emerged to help machines make decisions. Research grew stronger with the creation of the Stanford AI Lab in the late 1960s. During this decade, Joseph Weizenbaum also developed Eliza, an early chatbot that simulated human conversation (early chatbot Eliza).
By the 1970s, Tom Mitchell introduced Version Spaces at Stanford, adding to AI’s toolbox. However, AI faced tough times during the 1970s and 1980s, known as the AI Winter, when interest and funding dropped.
Things turned around later with better computers and more data storage. Machine learning became a big part of AI in the late 20th century. Then, in the 21st century, deep learning took off using advanced neural networks. Since 2014, generative models like GANs have also made waves in AI research.
Today, AI touches many areas like healthcare, finance, and entertainment. Governments and companies worldwide now pour money into AI to keep up with its fast growth. From ancient dreams to modern tech, AI’s story keeps evolving.
