Disney is using new deep learning software to analyze movie-goers’ facial expressions and gauge how much they’re enjoying a film.
The innovation within the new system is an algorithm that Disney and Caltech call factorised variational autoencoders (FVAEs), which use deep learning technology to automatically turn facial expressions into numerical data, and is able to incorporate metadata.
Combining the FVAE algorithm with infrared cameras, Disney can analyse the facial expressions of moviegoers in a cinema as they react to what they’re being shown on screen. With enough information, the new technology can even predict how an audience member will react to upcoming scenes after just 10 minutes of observation.
Why It’s Hot
- Technology could be used to tailor a film to an audience in real time, bringing in a new aspect of personalization to cinema
- Data gathered and analyzed can be funneled into other developing AI systems where picking up cues from their body language to be able to better assist (e.g. robot babysitters)
- Raises the question of how this will impact the movies we end up being exposed to with this AI now acting as the gatekeeper between us and the next Sharknado
“Inspired by service-design overhauls at companies such as Disney and Carnival, CVS is hoping to rethink the entire pharmacy experience.” The chain recognized that it needed to do more to give its customers a reason to visit their brick and mortar locations (not a unique problem facing retail right now, but unique in that CVS deals in prescription drugs). So instead of focusing on just one problem or one solution, they’re looking at a complete overhaul of the experience, with the goal of increasing loyalty and adherence – repeat trips to the pharmacy, and repeat retail purchases.
They’ve started the journey by hiring designer Deborah Adler (she’s behind the pill bottle color coding system used by Target and later declared a “Design of the Decade”). The revised take on CVS’s bottles allows patients understand at a glance when they need to take their medication and how much.
And there’s a huge amount of data driving this design decision. “The first, most important part is a system that understands what medicines should be taken together,” explains Kevin Hourican, CVS’s EVP of retail pharmacy. This is a massive data challenge that involves being able to scan thousands of different variations of prescription—”1x every day,” “once a day,” 1x every 24 hrs”—and then slot them into four basic day parts: Morning, Midday, Evening, and Bedtime. It requires verifying that those day parts are in fact right. And then it requires making sure that there are no dangerous drug interactions and that every drug is taken at its optimal time. (For example, blood pressure medications are best taken in the morning; cholesterol medications are best taken at night.) CVS’s system for doing all those calculations, Script Path, is the first of its kind.”
Why it’s hot: This is another example of a brand taking a more holistic, end-to-end experience approach to loyalty and marketing, and using data to inform what will (hopefully for CVS) be a ground-breaking design solution. This approach could open doors to additional marketing opportunities and collaboration for our healthcare clients, too.