1956

1957

1990s-2000s

2010s

2020s

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IBM produced a nice graphic for this nesting. Highly recommend their AI page as a good definitional starting point. Check out:

https://www.ibm.com/topics/artificial-intelligence

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A Brief Timeline

1950 thru 1960s - Birth of AI (It’s all there in theory)

Early AI research has its first intuition that computer algorithms should be modeled on the human brain to create systems that might one day ‘learn’. Artificial Neural Networks (ANNs) get their first definition and formal tests. And the Singularity idea is already conceived by Irving J. Good. The future was already here, just not yet evenly distributed!

Milestones:

1943: McCulloch and Pitts propose the first mathematical model of a neural network.
1956: The term "Artificial Intelligence" is coined by John McCarthy at the Dartmouth Conference.
1957: Frank Rosenblatt (not surprisingly, a pyschologist and computer scientist) invents the Perceptron, the first artificial neural network capable of learning.
1957: The General Problem Solver (GPS) created by RAND Corporation. Intended to function as a universal problem-solving machine, was ahead of its time.
1956: ELIZA, a natural language processing program, is created by Joseph Weizenbaum at MIT. Not ready for prime time, but points the way.
1965: Alexey Grigorevich Ivakhnenko demonstrates what a layered set of perceptrons could do, and thus demonstrates the earliest known example of a deep artificial neural network. ‘Deep’ refers to information passing through many layers of neurons where the data moves successively in stages to the final output, getting filtered and fitted along the journey.

1970s thru 1980s - the Era of Expert (Symbolic) Systems

Due to the limited early success of ANNs, and the successive national funding cuts computer scientists shift their focus towards expert systems and symbolic AI.