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8 Key Moments from the History of AI
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8 Key Moments from the History of AI

There has been a 270% increase in AI application among global businesses from 2015 to 2019. In fact, nearly 37% of businesses today leverage AI in one way or the other while 80% of all emerging technologies are projected to be based on AI by 2021. So while the future of AI seems accelerating, here are 8 key instances from its past to truly show how far it has come.

Warren S. McCulloch’s and Walter Pitts’ paper published in the Bulletin of Mathematical Biophysics, described artificial neurons and their ability to mimic the human brain, to a point where they may be able to perform simple logical tasks. This was the first step towards conceptualizing neural networks.

Scientist John McCarthy coined the term ‘artificial intelligence’ in a proposal that he presented at a summer conference. The term encapsulated different kinds of machine intelligence concepts like neural networks and natural language.

Psychologist Frank Rosenblatt built the Perceptron, a basic model of an artificial neural network that could recognize patterns. The New York Times described the Perceptron as “the embryo of an electronic computer that [the Navy] expects will be able to walk, talk, see, write, reproduce itself and be conscious of its existence”.

Arthur Lee Samuel, an American pioneer in computer gaming and AI, coined the term ‘machine learning’. He defined it as the “field of study that gives computers the ability to learn without being explicitly programmed”.

Prominent mathematician Sir James Lighthill submitted a report to the British government, questioning the ROI on AI research. He believed that tasks like common sense reasoning, face/speech recognition seemed beyond AI’s capability. This reduced government funding drastically. The DARPA (Defence Advanced Research Projects Agency), which had been funding AI research free-flowingly, now required that research proposals come with defined timelines and deliverables.

IBM’s supercomputer Deep Blue, defeated world chess champion Garry Kasparov. In a six-game series, Deep Blue won two games, Kasparov one, and three resulted in draws. As an impressive leap forward, this proved AI-powered machines could think strategically.

On the US television trivia show ‘Jeopardy!’ IBM’s Watson defeated reining champions, Brad Rutter and Ken Jennings. This was a greater challenge than playing chess as the show required contestants to answer complex questions and riddles. Watson was trained for three years to identify question-and-answer patterns, and the victory was hailed by many.

Google DeepMind’s AlphaGo – a neural network model – defeated the world’s greatest Go player, Lee Sedol. 60 million viewers watched the match live and saw world champion Sedol losing four games to one. The software had learnt the game by playing thousands of games against other AlphaGo versions.