Check How AI helps in Films & TV
Key participants in this market include streaming services and conventional movie studios. Industry heavyweights like Netflix and Amazon Prime are expanding their market share with AI-powered products. The following examples of AI applications in the film and television sector:
- User Experience:
- Content recommendation: Recommendation engines can predict what should be promoted to users at a given time by looking at customer watching data, search history, rating data, duration, date, and the sort of device a user uses. These referrals have led to unexpected successes like La Casa de Papel. A wonderful example of tailored targeting in action is Netflix’s landing cards. Based on user data, Netflix employs machine learning to present numerous landing cards for various categories. Their machine learning model is constantly evolving as a result of data obtained from A/B testing and data obtained during model training.
- Search Engine Optimization: Machine classification techniques help categorise movies more effectively, improving search results when users enter category names rather than movie titles.
- Automation of subtitle verification: Businesses can use neural networks to match subtitles to frames. Machine learning algorithms do this by extracting audio from videos and feeding it to the trained neural network. According to a case study, the laborious and time-consuming manual verification procedure is synchronised with machine learning.45 seconds, on average, for a TV show
less than 2 minutes for a typical movie
- Streaming quality: Because of AI, Netflix is able to forecast future demand and place resources at advantageous server locations. Users can stream high-quality video even during peak hours by pre-positioning the video assets closer to the subscribers.
- Automating content creation is a possibility for businesses. Algorithms based on machine learning and artificial intelligence can write movie characters, summaries, and script ideas. AI for content automation is becoming more popular thanks to tools like GPT-3.