Netflix Turns to Amazon Cloud for Movie Suggestions

Netflix has revolutionized the way we watch movies by delivering streaming video content to any device in your home. The executives at Netflix have decided to take this a step further and utilize cloud resources that will help you spend less time looking for movies and more time watching them. The project was once called “Netflix Prize.” In efforts to continue this project, Netflix has tapped the shoulder of the world’s leading data scientists and tasked them with finding an algorithm that will help you figure out which movies you’ll like without watching them or reading the reviews yourself.

The process of this task is called deep learning. Deep learning has roots going back to the mid-1970s and early 1980s. In those days, artificial neuron networks were created that mimicked brain activity. The process of deep learning has matured tremendously since that time. Google is known for advancing the process of deep learning. One of the most evident examples of this is the search engine suggestions proposed by Google when you begin typing in a search term.
Netflix is taking all of this a step further. With Amazon AWS, Netflix looks to use public cloud services in order to perform the task of deep learning in regards to its customer’s viewing habits. At first glance, this task may seem like it will require a tremendous amount of processing power. Netflix plans to use Amazon’s cloud GPUs in order to handle all of this data much more efficiently. Once a person has watched a couple of movies, the algorithm detects and suggests other movies based on the user’s rating of the movies they’ve previously watched.
Netflix is carrying the torch in cloud GPU deep learning algorithms. This news is exciting because services like Amazon will allow small to medium enterprises to use the services of a GPU farm without having to buy out infrastructure of their own. This can give small to medium enterprises an edge when it comes to business intelligence that they may not have previously been able to obtain in the past.