Today, machine learning has expanded far beyond simple games of checkers. Although there is still room for innovation, this technology has seen tremendous improvement. And with its many applications, it is moving into the public consciousness as well.

 

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Machine learning isn’t a new concept. The term itself originated in the 1950s. Arthur Samuel from IBM coined the term based on his research on computer checkers. In a game between a computer and a Connecticut checkers master, the computer won. This outcome opened up a world of possibilities.

 

Today, ML has expanded far beyond simple games of checkers. Although there is still room for innovation, this technology has seen tremendous improvement. And with its many applications, it is moving into the public consciousness as well.

A Quick Overview

Machine learning involves using data to teach computers to learn and improve independently. Its pioneer Arthur Samuel defines it as “the field of study that gives computers the ability to learn without explicitly being programmed.”

It is a field under artificial intelligence (AI), which is the capability of machines to make decisions akin to human behaviour.


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Scientists can jumpstart the machine learning process in different ways. It can be through data, examples, or system experience. The end goal is for the computer to pick up on the information and learn without human intervention.

Who Is Using It?

Machine learning and AI have a pretty broad scope of applications. These past years have especially seen unprecedented growth in this technology.

More and more industries are using ML in their operations. In 2021, 57% of companies across different sectors reported AI adoption. This figure is a 45% jump from 2020, implying a rapid adoption rate in businesses worldwide.

Machine learning technology can have boundless applications, as research is still ongoing.[…]

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