"Machine Learning" has been a buzzword in the tech space recently, but do you really understand how it works?

This article is based on one of our founders’ talks about machine learning. Our CTO Albert Padin, Google Developer Expert (GDE) for Machine Learning, was once asked to talk about machine learning to a group of kindergarten students in Singapore. This was how he explained it.

You know what a lion looks like.

You also know what an elephant looks like.

You know this because you’ve seen examples of a lion and of an elephant- you’ve seen it either in real life at the zoo, in movies, or photos on the internet. You recognize what an animal is when you have been shown what it looks like.

A machine learning model learns the same way. When you give examples (data) to a machine, it learns over time.

If you show a machine lots of pictures of lions and tell it these are lions, it will then be able to tell what a lion is. If you show it pictures of elephants and tell it these are elephants, it can then identify elephants on its own.

In another example: A gamer who has died multiple times on the same boss battle with repetitive attack patterns will eventually know how to counter and defeat the boss.

As humans, though, we need to sleep. And we forget sometimes. Computers don’t.

They have much more memory (which can always be upgraded), they don’t forget, and they don’t need to sleep. In 5 minutes, computers can process data that humans take 20 years to gather.

This is the advantage of machine learning over our mental processing capacity. Machine learning models process data at the same time you feed them the data, then they can immediately start identifying and processing similar data on their own with that knowledge.

This is why companies around the world are racing to harness Machine Learning to improve business performance. The technology empowers innovation that brings highly significant results.

We hope this article helps! Now you’re ready to explain to your friends- and preschoolers- how machine learning really works. *robot wink*

Read the story of how machine learning saved us 4 months of work to classify 200,000+ images

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