AI in Media and Entertainment Industry: Application & Use Cases
The media and Entertainment industry is also utilizing the power of Artificial Intelligence (AI) in making the visual content more interactive and interesting.
It is helping to serve the audience a data-intensive and personalize automated content making their viewing experience more interesting and entertaining.
While on the other hand, the entertainment industry needs such innovative technology to make the audience experience more enjoyable and user-friendly.
AI companies are also consistently working to integrate this technology into various sub-fields of the entertainment sector improving its efficiency.
AI Applications in Media and Entertainment
The application of AI in media and entertainment is witnessing rapid growth especially in terms of distributing and showing visual content.
Media companies face challenges while developing the content in high quantity while ensuring the quality, hence they adopt AI to achieve this objective.
And once they achieve their objective, they improve their services enhancing the experience of the customers. So, we have discussed here the use of AI in the media and entertainment industry with use cases and examples.
Personalizing the Content & Recommendations
From music app to OTT platforms, the audio, as well as visual contents, can be personalized as per the preferences and previous experiences.
Using machine learning, users behaviour and demographic details, music or videos are recommended like what kind of movies they like most.
AI using advanced machine learning algorithms and deep learning networks helping in delivering personalized content to users.
And this kind of highly personalized experience for users helps media or entertainment companies increase their user base and offer a better service compared to their competitors.
Online Advertising with Targeted Audience
Online advertisements in the media industry are playing a significant role in branding and business promotions.
And AI is used to make online advertising more precise and productive with a targeted audience for higher conversion rates.
The best example is Google Adsense and Adwords that can use the user’s history like what kind of products they were searching for or browsing on web or eCommerce sites.
And this kind of AI-based sensing helps AI to show the ads as per the user’s preferences. It helps advertisers to target the right audience and get maximum outputs from the Ads.
Controlling the Online Broadcasting Content
The online media and entertainment industry is running with the help of different types of content.
And apart from general topics or common subjects, there is objectionable content broadcasted through TV, Online Music Channels or OTT platforms.
Controlling such content is mandatory from the regulatory authorities. Again AI helps here in detecting and filtering such objectionable contents.
AI can identify the user’s age and gender before showing such content or using the automated content moderation service to moderate the objectionable content before broadcasting with the audience category ratings like 7+, 13+, or 18+.
Classification & Categorization of Content
Online streaming platforms like YouTube or OTT have different genre of music videos, songs, movies or TV shows.
And these online platforms are using AI algorithms to show the content as per the user’s preference and choice.
The AI-enabled system can detect the objects, data, visual scenes and other details about the movies like genre, cast and crew members to show them similar content.
Implementing the AI in media and entertainment industry can automate the categorization and classification of content for a better users experience.
Meta Tagging Subtitles & Automated Transcription
Content published in the media and entertainment industry needs to make comprehensible to the audience. Hence, AI can help in identifying the videos and other online content to classify them with meta tags and descriptions.
Apart from that movies, music videos and TV shows are transcribed into different languages using AI-based technologies like natural language processing through machine learning and deep learning.
The voice of movies is converted into different languages with subtitle and audio annotation to make it understandable to a wider populace for more engagements of the users.
Customized Chatbots for Virtual Assistance
AI-based virtual assistance is also playing an important role in the media and entertainment industry.
OTT and online music platforms are assisting their customers to solve their queries and offer a hassle-free music experience.
These AI-based virtual assistance applications are also helping the media companies gather useful chatbot training data like users preference, their experience while using your service or any kind of other suggestions regarding your online platform.
And this data is also used to train or develop the chatbots developed for the media and entertainment industry to improve performance. That eventually helps these companies offer better service to their customers.
Detecting & Controlling the Fake Content
Apart from original news posts, many websites publish and circulate fake news to provoke the audience towards certain events or social issues.
AI is helping here to detect and control such content and helps the online platforms like social media sites owners to moderate or remove the content before circulation.
And not only the text content but images and videos are also created using the deepfake technology.
But with the help of depfake detection service, we can identify the fake images and videos reporting the regulatory authorities to take appropriate actions such as creators helping our online community away from such fake things.
Social Media Platform for Sentiment Analysis
Unofficial media sites like social networking platforms and messaging applications providing a free place for to users share their opinions and views on different topics.
Analysing such discussion of different age group or people from different regions or demographics provides useful insights about the different people.
To analysis the content published on social media sites, sentiment analysis is the technique used by many companies.
And once such data is gathered, is again used for machine learning to develop the AI model that can analyse the sentiments and feelings of people interacting with each other unofficially at such platforms.
With these AI use cases in media and entertainment, I think you get an overview of how AI applies to various sub-fields. However, for developing all types of AI applications or systems you need a huge amount of machine learning training data.
As much as training data is available to develop the model the performance of AI would be better helping the users get the best results in various scenarios.
This article was originally written & featured at www.cogitotech.com
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