If you’re keeping up to date on technology news, you’re probably seeing references to machine learning everywhere, and for good reason: machine learning is an integral component of the way that computers process information.
Machine learning is all around us, informing our day to day lives from the way we navigate Google maps right down to the way we check our inboxes.
But what is it exactly, and when did it start being such a big deal?
Here’s a quick explainer to get you up to date:
SEE ALSO: Thousands of people open a trivia app twice a day for the chance to win hundreds of dollars — here’s how you play
There have been two especially important developments in the history of machine learning: the first began with artificial intelligence pioneer Arthur Samuel, who coined the term “machine learning” back in 1959.
In 1959, MIT engineer Arthur Samuel described machine learning as a “Field of study that gives computers the ability to learn without being explicitly programmed.” Samuel was busy creating his own computing machine: an autonomous checker program that he envisioned would someday beat the top world checker player champion.
The other important development in machine learning? The internet.
The advent of the internet presented a trove of accumulated data. With so much information readily available, there seemed but one thing to do: figure out a way to organize it into meaningful patterns — one of machine learning’s most integral roles.
Big data is the fundamental building block of machine learning.
Big data, is, essentially, exactly what it’s called: a ton of data. It’s all of the information accrued by social media companies, search engines, and even microphones and cameras that are constantly collecting information.
See the rest of the story at Business Insider
Source: Tech Insdier