{"id":21115,"date":"2018-09-19T06:30:57","date_gmt":"2018-09-19T13:30:57","guid":{"rendered":"https:\/\/insidebigdata.com\/?p=21115"},"modified":"2018-09-20T08:51:51","modified_gmt":"2018-09-20T15:51:51","slug":"entertainment-industry-ai-tools","status":"publish","type":"post","link":"https:\/\/insidebigdata.com\/2018\/09\/19\/entertainment-industry-ai-tools\/","title":{"rendered":"Trends in Entertainment Industry Push Enterprises Toward AI Tools"},"content":{"rendered":"

This is the second entry in a five-part\u00a0guide series<\/a>\u00a0that explores how artificial intelligence is revolutionizing and evolving the media and entertainment industries. This post explores how trends in the media and entertainment industries are leading enterprises in this sector to increasingly adopt AI tools.\u00a0<\/em><\/p>\n

\"AI<\/a>

Download the full report. <\/a><\/p><\/div>\n

Trends<\/strong><\/h2>\n

As volumes of structured and unstructured data continue to grow almost exponentially, and the cost of the technologies needed to wrangle and exploit that data \u2014 namely data storage and computing power \u2014 fall, organizations across the media and entertainment industry (ME&I) are turning their attention to AI. The behavior of non-player characters (NPCs) in video games is one well-known example of AI algorithms at work. Often serving as important plot devices (i.e. advancing the storyline in a specific direction), these NPCs can have a profound impact on player experience. As any gamer can tell you, that impact is dictated by the quality of the AI. Moreover, predictability can strike a death-blow to a game\u2019s repeatability, or profitability in the case of a franchise. AI tools and technologies such as facial, speech and object recognition are also changing the way players participate in the games \u2014 from avatars that reproduce a player\u2019s movements onscreen, to fully immersive Artificial Reality environments.<\/p>\n

Within the film industry, the on-screen realization of an AI-driven approach to digital effects is impressive. Equally impressive is the potential for the technology to reduce critical time and cost during the pre-production process. For example, using language processing to breakdown a script ready for storyboarding, or using data from previous productions to model an optimized filming schedule. Automating these types of processes has the additional benefit of freeing up the production team for more creative tasks.<\/p>\n

And then there\u2019s the evolution of AI tools within the music industry. From composition to digital processing, algorithms are moving from \u2018tool\u2019 to \u2018collaborative partner\u2019. The collation of on-demand television programs, conversion rates on digital newspaper articles, AI-based analytics within sports broadcasting \u2014 the list of potential (and current) use cases goes on. So what impact is this having?<\/p>\n

Impact <\/strong><\/h2>\n

Content generation <\/strong><\/p>\n

An AI-driven approach can empower the creative process, offer the opportunity to explore \u2018what if\u2019 scenarios, and bring visuals to life. In the case of Virtual Reality where players typically wear a display and headphones for an immersive experience, and Augmented Reality where realworld elements are combined with virtual ones, the results are compelling.<\/p>\n

Pok\u00e9mon Go is a perfect example of Augmented Reality in action. Players of the game use their mobile devices to track down 2D cartoon Pok\u00e9mon, which appear in real-world surroundings. Their locations, frequency, and manifestations are all dictated by algorithms. The game has proven to be incredibly popular, and a notable nod to the fact that the way people consume media and entertainment content is changing.<\/p>\n

Take the popularity of mobile app Snapchat, for example. Behind the quirky filters lies complex machine learning algorithms. Facial recognition enables the app to detect a face, recognize facial features, and create a 3D mesh that overlays the image over specific coordinates on the face, moving with it. In other words, people can pose and take a photo of themselves with the features of a cat (ears, whiskers, tail, etc.) blended somewhat seamlessly over their own features.<\/p>\n

More recently, the app has begun to provide the option of recognizing features in a photo, and then using that as the overlay. From personal experience, the results can be somewhat disconcerting. But there\u2019s no denying that the technology is compelling. Fellow mobile app Mug Life hopes to tap into that trend by using deep learning to enable users to upload any photo, and then instantly create a 3D animation.<\/p>\n

Algorithms are able to deliver content in a personalized way. For advertisers, this offers the chance to precisely target audiences based on the media they consume, increasing the chance of conversion.<\/p><\/blockquote>\n

Content management and delivery <\/strong><\/p>\n

Just as content generation can benefit from AI, so too can the management and delivery of that content. Most avid collectors of media \u2014 movies, for example \u2014 can tell you that too much choice can, in fact, be a bad thing. From content-based searches, to content suggestions based on selections over time, algorithms are now able to condense that choice through the delivery of content in a personalized way. For advertisers, this offers the chance to precisely target audiences based on the media they consume, increasing the chance of conversion. It\u2019s worth noting the significance of the fact that AI is closing the\u00a0loop between audiences; content generation, management and delivery; and the subsequent consumption of that content. AI offers a deeper level of audience insight that can inform the content production process, from creation to marketing strategy.<\/p>\n

Stay tuned; this\u00a0guide series<\/a>\u00a0will also cover the following aspects of AI in the media industry over the next few weeks:<\/p>\n