Let’s look at some stalwarts who planted seeds in fields when AI was not relevant to day-to-day work. Today, these seeds have become a global forest with large trees.

While there are many such, I will cherry-pick a few to discuss how AI preparation evolved.

Alan Turing:

A British Mathematician, marked as the pioneer of AI, showed us the path to Machine Learning.

While researching computational science, he came up with the idea that the Human Brain makes a lot of its decisions based on some computational logic, our mental algorithms, and information that we receive. He suggested that a similar decision-making process or algorithm can be replicated in machines to make a machine think and decide.

In his 1950 Paper “Computing Machinery & Intelligence,” he raised a valid question: Can Machines think?”

This question was the first few steps towards Machine Learning & Artificial Intelligence, where a machine can make decisions based on algorithms like & AI can mimic human behaviour intelligently.

There was no terminology like “AI/ML” yet; it was only a question & Hypothesis.

They say a good question can uncover a new world.

John McCarthy:

An American Computer Scientist, we call him “the father of AI.”  He coined the word “Artificial Intelligence” in 1956 during the Dartmouth Summar Research Project.

He received the “Turing Award” in the early 70s to continue his quest for AI.

In his article “Ascribing Mental Qualities to Machines,” around the late 1970s, he suggested that a machine can have beliefs. This article gave rise to a decade-long intelligent debate on how a machine can’t have a belief system, as a machine is not conscious and lacks the intention to provide context to any belief system.

Today, machines talk to each other, and machines talk to humans; they interact, communicate, and act.

Frank Rosenblatt:

Mr Rosenblatt was an American Psychologist who took his neural research on human intelligence to a different dimension, towards artificial intelligence.

In the early 1940s, Warren McCulloch, another psychologist, and Walter Pitts, a computational Neuroscientist, developed the algorithm “Perceptron” for machine learning (Binary classifiers). Frank Rosenblatt then implemented the algorithm.

In his paper “Perception: A Perceiving & Recognizing Automation” (the late 1950s, arguably 1957), he suggested the feasibility of an electronic or electromechanical system that could mimic human brain capabilities in terms of pattern recognition and prediction through learning information provided to the machine rather than fitting a pre-decided logic (Programmed Vs Intelligent).

He implied that statistical models can be used to make future predictions. This laid the foundation for the development of Deep learning techniques, which are advanced methods of Machine learning used in many AI-powered applications.

A few more significant stalwarts who contributed to cybernetics and forecasting techniques were Alexey Ivakhnenko and Valentine Grigorovich Lapa, two brilliant Soviet Mathematicians around the late 1960s.

The list is not exhaustive; rather, it indicates that AI was in bright minds long before taking control of the world.

These researchers did not have enough data, framework efficiency, industry focus, the Internet, funding, or inexpensive hardware, but how an idea can go so long is a matter of imagination that is feasible in the future. Never underestimate your imagination!.