How Netflix using AI to conquer the digital world

Netflix is commissioning original content because it knows what people want before they do.

Netflix uses its in-depth information, driven by AI to convince the top talent in the world of TV and elsewhere to join its ranks as staff, partners and content creators. Some broadcasters are not far behind in the skills race. Netflix not only has the largest subscriber base for any business but has managed to continue to grow. Its market capitalization competes with Disney, which is the world's most important entertainment company.

So what is Artificial Intelligence?

Artificial Intelligence (AI) is a field of computer science dedicated to solving cognitive problems that are often associated with human intelligence, such as learning, problem-solving, and pattern recognition. Artificial Intelligence, often abbreviated as "AI", may include robots or scenes of the future, AI extends beyond science fiction cars, has become one of the most sophisticated computer science fiction today. Professor Pedro Domingos, a leading researcher in the field, describes the “five nations” of machine learning, artificial intuition, of philosophical origin and philosophy; connectors, derived from neuroscience; mutations, related to the biology of evolution; Bayesians, working with statistics and opportunities; and illustrates the scientific background of psychology. More recently, advances in mathematical efficiency have led to the success of the Bayesian people in advancing the field in many areas, under the term "learning machine". Similarly, advances in network census have led to coordinators advancing the area under the term “deep learning”. Machine learning (ML) and deep learning (DL) are both computer science fields based on the Artificial Intelligence discipline.

But how could Netflix possibly know which genre best fits the tastes of the user?

Why Netflix uses Artificial Intelligence?

• Thumbnail personalization: 

Icon guessing has made it and made it easier for users to choose their favourite movies. Most users usually choose movies or series based on an icon to find out if they should watch a movie or not. Over time Netflix realizes that the theme alone cannot convince the user to watch a movie, so, their appearance is a powerful personal icon. 

All selected icons are designed with an algorithm, in which users' preferences are selected, and based on previous viewing history, the selected icon has a very high conversion rate. 

In all Netflix programs, there are a variety of posters each that caters to a specific group of viewers. As the algorithm collects data and information to the user based on thumbnails, it provides a better response to identifying the type of users. Netflix Annotation: Netflix creates metadata for each frame including brightness. 

Netflix Image Level: Netflix uses metadata to select certain high-quality images (good brightness, motionless blur, perhaps contains bulletproof face shots from a reputable section, does not contain unauthorized content, etc.) and is highly clickable.

• Optimal streaming quality:

Stream quality is an important metric that contributes specifically to return rates. With over 140 million subscribers worldwide, it is a challenge for Netflix to provide the best streaming quality to its viewers. However, with the help of AI and machine learning, Netflix can now predict future needs and place assets in strategic locations ahead of time. By prioritizing video assets near subscribers, viewers can stream high-quality video even during peak hours without interruption.

• Tailored movie recommendations made just for you:

Although two people are logging in to Netflix at the same time, both will be given different program recommendations. While this may seem obvious on the face, however, the inner story is completely different. The Netflix recommendation system works based on an algorithm, but a major factor that increases the compliance of these recommendations is due to machine learning and AI. The algorithm reads as data is collected. Therefore, the more time you spend on Netflix, the more relevant programs will be recommended.

So what Netflix does with user-created data?

Netflix Uses Data To Create A Limit Of User Profile Interests

Yes, they use it to compile a 360 profile for each user and statistically identify each user according to hundreds, maybe thousands of different features of user interest including movie type, favourite characters/characters, movie title, etc.

They do this in an attempt to bring people with similar interests together so that they can use data from one user to help predict possible behaviours of other similar users.

What Experience does Netflix gain from all users data?

Now that we know how Netflix converts images into digital learning models, what is the understanding that Netflix has gained from all the data processing and A / B testing they have done for so many years?

Yes, in addition to reading the millions of icons that have converted users into loyal subscribers over time, here are a few additional things Netflix has learned about working with icons:

• Show close-ups of emotionally expressive faces
• Show people villains instead of heroes
• Don’t show more than three characters

The conclusion:

75% of users choose movies based on company recommendations, while Netflix wants to make that number even higher.

Netflix has done an amazing job of using AI, data science, and “real-time” learning tools using a product-based approach that focuses on business needs first, and then AI solution next, rather than the other way around.

Technology experts may be inclined to offer existing AI solutions, but the most effective way to embrace AI is the way Netflix has acted with a business-driven first impression.

As the world of AI, data science, and machine learning continues to grow, we product managers can all take a lesson or two on how Netflix deploy AI solutions.

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