How My Team and I Are Trying to Revolutionize Hollywood
A lot of people ask me about what I do at USC’s Entertainment Technology Center, and I’m really proud of what my team and I have built in just under one year, so I thought I would share the scope of our work below, and a description of some of the projects we’ve been working on.
ETC is a phenomenal place to approach technology problems in entertainment. Because it is housed within USC’s famous School of Cinematic Arts - without a doubt the best film school in the world- and is chaired by the most senior technology executives in all the studios, it is a very unique forum to discuss tech challenges and quickly prototype and implement industry-wide solutions. I don’t know a single other place where a team like mine can research an industry problem, discuss and architect a solution with all players of that industry, then have that solution built and implemented at an industry level in a matter of months.
As you can tell, I’m very proud of working there, and we’ve been working very hard to solve massive problems throughout the industry, so I thought I would share this with you. Huge shoutout to my amazing team: Marcello, Hank, Harsh, Jonluca, Chris, Melanie and Stephen, and to the wonderful ETC staff: Ken, Edie, Eileen, George, Phil, Erik, and Erick. Very special thanks to SCA Dean Elizabeth Daley, who has been the best boss I ever had, who loves film more than anybody else I have ever met, whose vision has really built SCA into what it is today, and - most importantly- has very gracefully put up with a lot of my team’s antics over the past few months.
Enjoy and get in touch if you want to know more or have questions.
The Data and Analytics Project aims to help the entertainment industry accelerate the deployment of machine learning and artificial intelligence solutions throughout its operations (from production to distribution). Through a problem-driven, “engineering-first” approach, the project focuses on researching, designing and architecting functional prototypes of systems, methods and standards that solve industry-wide problems in an inter-operable manner. The problems we currently focus on are some of the largest in the industry, and include: developing a deeper, more semantic understanding of entertainment audiences and the stories that resonate with them, creating AI-driven platforms crunching large-scale data to help studios make better greenlighting, scheduling and marketing decisions, deepening insights about foreign (especially Chinese) film audiences, and applying neural-symbolic reasoning methods to develop fine-grained, semantic and symbolic knowledge representation and machine learning architectures for content recognition and warehousing.
“The Storytelling Cipher: Mapping Precise Story and Character Mechanics to Box Office Returns”. This study leverages the Dramatica taxonomy of film narrative to infer which scene-level character and story attributes generate more box office returns, by genre. We are extending this study to ads and movie trailers.
“The Influencer Project: Finding, Scoring and Activating the Most Valuable Fandoms”. This project seeks to develop a brand new methodology to granularly measure how valuable TV and film fan communities are on Reddit and Tumblr by looking at how far outside their core communities they are willing to spread the word about the title they are passionate about.
“Interestingness and the Theory of Novelty”. This study researches concrete applications in film and TV for Jurgen Schmidhuber’s cognitive theory of interestingness, which seeks to quantitatively explain why we find certain things more interesting than others. We have prototyped the world’s first production-ready system to score the interestingness of any idea, person, film, TV show, or brand.
“The Theatrical Demo Data Project”. This project is testing a new, in-theater technological solution to collect large-scale data on the demographics of film audiences film by film, show by show, in real time.
“The Chinese Film Audiences Study”. This project seeks to develop large-scale technological solutions to collect data on Chinese film audiences through a semantic analysis of film-related conversations in China.
“The Intelligent Windowing and Scheduling Project”. This project seeks to architect a platform to crunch large scale data to make better windowing and scheduling decisions.
“The Unified Data Structure Project”. This project seeks to develop advanced standards and solutions to solve the industry-wide problem of exploding content formats, data types and taxonomies, through a combination of in-RAM hypergraphs database structures and neural-symbolic reasoning methods drawn from Artificial General Intelligence.