August 26, 2020
There's a lot we can learn about machines, and there's a lot machines can learn about us, too! Ever wonder how virtual personal assistants or dating apps work? Or how Netflix picks the perfect show for you? They're learning from you by optimizing and building upon human-created algorithms. Each text you type, person you swipe, or show you pick is stored as data, and through a process called machine learning, that data is plugged into algorithms to streamline your next texting, dating, or show-picking experience.
Let’s take any entertainment streaming service. It stores information about the titles you’ve watched, like genre, actors, year, category, and how (if) you rated them, in order to recommend other titles you may also enjoy. It also considers what other titles members with similar preferences have enjoyed. All of this data is stored and used as input in algorithms, which are sets of rules that solve a problem. The problem, in this case, is that you might like to have a new show to watch.As you continue interacting with your entertainment streaming service, the better the recommendations will be, because the more data it has on what you choose to watch.
Yes! Well, it’s learning what humans tell it to learn. The same way we might read through a book given to us to study and memorize course material, the computer gathers and stores the data we tell it to store. However, we can choose to go beyond that book and learn from other sources by running an internet search or asking others. The machine lacks the intelligence to do this on its own, but if it was programmed to do so by a human, it could.
Wikipedia defines machine learning as “the study of computer algorithms that improve automatically through experience.” The key word here is “automatically.” A human manually sets up an algorithm that the machine uses to come to conclusions, but the more data the machine has, the more it has to “learn” from to improve its conclusions, without the need for a human programmer. However, the machine is only improving upon the algorithm, optimizing the output it gives with the more data it has, and not creating its own algorithms. Humans will always be needed to tell the machines what to do.
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