The origins of artificial intelligence can be traced back to ancient myths and legends, where there were stories of statues coming to life. Throughout history, philosophers, mathematicians, engineers, and many others have contributed to the development of AI. Some important milestones in AI include the work of Alan Turing and the invention of transformer neural networks.
Notable early figures who tried to explain human thoughts as symbols, which laid the groundwork for AI concepts like general knowledge representation, include Aristotle, Muhammad ibn Musa al-Khwarizmi, Ramon Llull, Rene Descartes, and Thomas Bayes.
The rise of modern computers began in 1836 when Charles Babbage and Augusta Ada Byron invented the first programmable machine. In the 1940s, John von Neumann developed the concept of stored-program computers, which store both the program and data in memory.
In 1943, Warren McCulloch and Walter Pitts published a neural network model that laid the foundation for advancements in AI today.
Alan Turing created the Turing Test in 1950 to determine a computer's ability to deceive humans into thinking it is human.
The 1956 Dartmouth conference, sponsored by DARPA, included AI pioneers Marvin Minsky, Oliver Selfridge, and John McCarthy. McCarthy is credited with coining the term "artificial intelligence." Allen Newell and Herbert A. Simon presented the Logic Theorist, the first AI program capable of proving mathematical theorems.
After the Dartmouth conference, leaders were hopeful that a thinking machine as smart as a human was just around the corner. They received a lot of support from the government and industry. For almost 20 years, there was a lot of progress in AI, such as the General Problem Solver algorithm, Lisp programming language, and ELIZA program.
But then, the development of AI systems as good as the human brain proved to be difficult. So, government and corporations stopped supporting AI research. This was known as the first AI winter, which lasted from 1974 to 1980. In the 1980s, there was a new wave of enthusiasm for AI with deep learning techniques and expert systems. However, this was followed by another collapse in funding and support.
The second AI winter lasted until the mid-1990s when neural networks and big data brought about the current AI renaissance.