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🎦 The AI behind your Netflix experience

From seamless streaming to personalized recommendations

The AI behind Netflix

Hey AI enthusiast,

Today’s edition revolves around Netflix and its use of AI to enhance your streaming experience.

For the few of you that don’t know it, Netflix is an American media company that offers a video-on-demand service.

So, you know how when you log in to Netflix, you see recommendations for new shows to watch based on what you've watched before? Netflix uses a technique called Collaborative Filtering to analyze patterns in the user viewing behavior across millions of subscribers. This allows them to predict what content you might enjoy and recommend new shows and movies to you.

But that's not all. Netflix is constantly improving how videos are streamed to your device, making sure it's smooth and seamless. They use Machine Learning to predict when there might be a slow internet connection at your location and adjust the video quality accordingly so that you don't experience any buffering or lag.

And finally, Netflix is also using AI to improve the video quality of their content. They employ a technique called Reinforcement Learning to train their algorithms to optimize video encoding so that it consumes less bandwidth and looks better on your device.

📚 AI Academy spotlight

Inside our Foundations of AI course, you’ll find an entire section dedicated to recommender systems and how they work with a special focus on their use in Netflix.

You'll be able to gain a deeper understanding of the technology that powers them.

If you're curious about the behind-the-scenes of this amazing technology and more foundational concepts of AI, you should definitely check out our course.

🧱 Foundational concepts: Reinforcement Learning

Reinforcement Learning is a type of machine learning where a computer program learns to make decisions by doing things and getting feedback in the form of rewards.

Just like how we learn to do things better by trying and getting feedback, the computer program tries different things and learns which actions lead to the best rewards.

The goal is to find the best strategy that gets the most rewards over time.

Besides optimizing video encoding as Netflix does, this approach is also useful for teaching computers to do things independently without being programmed explicitly, like playing games or driving cars.

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