Artificial Intelligence in the Entertainment and Media Industry

 The media industry and global entertainment witnessed a rapid transformation in the way content is distributed. More and more content creation such as high-resolution cameras, content making software, and smartphones allow almost everyone to make, publish, and distribute video, audio, and video content.

This trend is increasingly accelerated by Internet proliferation, which has replaced traditional media channels such as cables and radios with on-demand streaming platforms such as Netflix and YouTube. As a result, consumers have potentially unlimited options to be chosen in terms of media consumption.

Thus, media companies need to increase the quantity and quality of their content to help them achieve this goal; media companies adopt advanced technology such as AI.

Here are some cases of use of AI in the media and AI in entertainment that changes the industry:

1. Tagging Metadata:

With countless content made every minute, classify these items and make it easy to find viewers into Herculean's duties for media company employees.

To perform this task on a large scale, media makers and distributors such as CBS Interactive use AI-based video intelligence tools to analyze video frame content with a frame and identify the appropriate object.

2. Personalization of Content:

The leading music and video streaming platforms such as Spotify and Netflix are successful because they offer content to people who have all demographics, have different tastes and preferences.

Companies like it use AI and machine learning algorithms to learn the behavior and demographics of individual users to recommend what most interested in watching or listening to next makes them continue to get engaged. As a result, this AI-based platform provides customers with content that meets their specific passions, offering them a personalized experience.

3. Reporting Automation:

In addition to automating daily operations or day-to-day, Artificial intelligence also helps media companies to make strategic decisions. For example, leading media and broadcasting companies use machine learning and natural language generation to make channel performance reports from RAW Analytics data distributed by Barc.

Weekly data usually accepted from the Indian broadcast audience research board (BARC) is generally in the form of thick Excel sheets. Analyzing these sheets every week to obtain and implement meaningful learning proved quite frightening for the Analytics team.

Using data analysis-activated AI and natural generation-based reporting automation tools, business leaders can create performance reports with language comments that are easy to understand, giving them accurate insights to make decisions driven by data.

4. Generation of subtitles:

They need to provide an accurate multilingual subtitle for their video content. Manually writing subtitles for several shows and films in dozens of languages can take hundreds or even thousands of hours for human translators.

In addition, it may also be challenging to find the right human resources to translate content for specific languages. In addition, human translations can also be susceptible to errors. Media companies use AI-based technology such as natural language processing and natural language generation to overcome these challenges. For example, YouTube AI allows the publisher to automatically produce closed text for videos uploaded on the platform, making their content easily accessible.

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In short

By exploring and experimenting with cases of use of AI above and others, media companies and entertainment maximize their business performance by increasing the user experience and entertainment value they deliver with greater efficiency.