Artificial intelligence (AI) is currently used in the entertainment industry. Combined with machine learning (ML) it can help networks and others get their content seen by the right people(1). It can also suggest to viewers what to watch next based on their interests. The key? Analyzing the metadata that’s used in the search optimization, ad targeting and recommendations.
How does machine learning help program AI?
By:
- Using natural language processing to analyze the dialogue in the TV show. To creates a series of themes
- Analyzing the dialogue between actors helps it and AI examine the mood and personality traits of the main characters which allows consumers to find specific scenes and episodes
- Gaining a deeper understanding of the video content. An example? The personality traits being displayed by an actor.
For example, Amazon uses AI to analyze scenes, objects and faces. It helps the company figure out what the viewers are clicking on.
When media and entertainment (M&E) businesses use ML, it helps them:
- build logo and brand recognition and
- determine how audiences are reacting to the content. The data can be used to market, personalize and stop consumers from switching to another service.
As AI starts using voice search in devices, the pay TV industry uses it to improve the viewer experience. An example? Food Network launching a search capability on Amazon voice enabled devices (Amazon Echo, Echo Dot, Amazon Tap, Amazon Fire TV). The viewer asks the devices about Food Network programs, schedules, recipes and more.
In the advertising world, AI can be used to personalize the content for the customer and advertiser. By using content intelligence, AI can examine what the viewers are watching and when and provides the advertiser a one to one marketing approach to the viewer.
Advertisers should consider AI as their partner that helps them analyze the data to find a fast solution (2). The pros and cons of using AI?
Pros:
- AI can be used for targeting and helping discover people to target the ads. It includes bidding efficiently for the ads and
- AI can be used to build B2B sales leads.
Cons:
- AI can’t answer questions that have a broad answer. For example, it can’t recommend which social media platform to use for an advertising campaign (there’s no consistent measurement across these platforms)
- AI can’t analyze data from consumer surveys or media consumption data. Media planners need to define the data before AI analyzes it and
- AI can’t write long ads.
In the film industry, AI helps a movie studio figure out whether or not to make the film by analyzing the screenplay. Or determines the box office potential of a film before it’s released by using a neutral network algorithm to analyze 30 years worth data (box office revenues, film budgets, audience demographics and casting information).
Here are two examples where AI was used to write a short screenplay or scene:
- an AI named Benjamin wrote the short film Sunspring by examining hundreds of movie scripts from the 80’s and 90’s. This is the first time an entire screenplay has been written by AI.
- In the film “It’s No Game”, AI was used to write David Hasselhoff’s line. The machine learning algorithm learned to create long sentences based on learning rules from a corpus (composed of dialogue taken from several collections of films and television series) of writing. Another algorithm was used to create short sentences from the words.
AI can automatically create an edited clip that can be sent to another company or given to a human editor to create the final clip. For instance, IBM Watson selected the 10 most usable moments from the horror movie “Morgan.” The human editor created the movie trailer from the clips. This was done in 24 hours instead of taking 10-30 days using a human editor.
As machine learning continues to evolve, media companies can use the technology to create other types of content such as series and movie reviews (AI can find the data from different reviews to see what the critics or consumers are saying about it on social media or online).
AI should be seen as a partner.
