Home Technology How AI is Changing The changing the face content in future AI

How AI is Changing The changing the face content in future AI

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How AI is Changing The  changing the face content in future AI

While many organizations and sectors align AI solutions for the first time, an industry has improved the algorithm and the completion of artificial intelligence – Media.

Large players in the media have managed to use personalization and smart algorithms for some time. Sharing a great appetite for the media industry for AI, Ted Sarandos, Head of Content at Netflix, said, “We have deliberately shown no personal brand mix.”

But the AI ‚Äč‚Äčapplication in the media is not just limited to content personality. The media team must handle the manual process for all – rather than providing media to create multi-subtitle subtitles.

But new developments in AI automate many of these tasks. Development of computer vision, speech for text and natural language change algorithms, make media, distribution and most importantly, media usage.

Search Voice

Sounds are the most natural way for people to communicate. Therefore, the use of voice search in the media increases.

While in India, voice is the dominant way to interact with computers – Google reports that Queries Hindi Voice 400% YoY. Media companies are interested in finding this claim – YouTube has voice and overnight search, Gaana also introduced voice assistants in mobile applications.

Sound questions are very different from traditional search. People ask like “Show me when Kohli makes a century” and try to find the right moment when Kohli scores. Traditional media can not do anything – game recording will be great, 4 hours plus monolithic files.

Some Kohli noted that the century was only a 2 minute clip on this file. This means that the clip must be created manually, which can not measure all questions that people will ask.
AI can change everything.

AI can analyze video frames with frames and quotes for words. Using face detection, AI can identify Kohli and the NLP algorithm can track the time when commentators announced the century. This determines the shortest portion of the video when it is likely that Kohli has calculated it for centuries.

This is a dynamically generated section, no manual edits, and can be played when the user returns a search query.

Media Conversation

Once the media can understand the voice interaction, it can start communicating with you. This is a great new way for this story.

Take a look at companies like Novel Effect, which creates a new experience of reading story books with children.

As you read books quickly, smart voice recognition remains parallel and AI automatically plays specially designed music such as thunder, violin or song at the right time to keep the children in the story.

The media is now talking to you, finding out and then creating something new. Is it still a book or another? What is the story or experience? AI is a traditional audio silo audio and video medium that can not be pulled and put it together into something different.

Adaptation Media

Personalize content all about suggestions. When recommending a video or audio you like, the media itself does not change for you.

In the future, the media will change itself and change it for you. With AI, production teams can provide more context to the media – location, user profile, file metadata and media-based can quickly change.

Try a simple example – There’s a rough movie. Traditionally, the editors will manually remove their clips to make it suitable for younger audiences.

Deep algorithms, in combination with calculus for text calculus, can detect the interactions and times used in the media automatically and appropriately.

The type of media accepts user input (the app can raise the question “What is your date of birth?” For users) and based on user input, dynamic viewers are not harmful if the user is under 18, though not. The keywords here are dynamic – happen quickly, without human intervention.

Awakening of Intelligence Content

Traditional media infrastructure can not support all of these cases and therefore make smart content the primary priority of all media houses.

Instead of storing media as a monolithic file that does not know, companies can get AI looking for files for smart labels, transcriptions and classifications. It makes the media fit and ready for the future of voice search and exciting new experiences.

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