Disney Research engineers have developed a machine learning software that can evaluate the various and complex emotional responses of movie audiences based on their faces.The software utilizes an algorithm called factorized variational auto-encoders, or FVAEs, and was developed in coordination with researchers from Caltech and Simon Fraser University. Usually, variational auto-encoders automatically transcribe the complex images they collect into numbers and is sometimes called latent encoding or representation. But this new FVAEs from the university partners' also add metadata, that is additional information about the data itself. When it comes to understanding faces, the FAVEs breaks down each expression by assigning a number to certain features then connects that number to matching expressions at other times or different expressions occurring at the same time. For example, one number may represent a small smile, while a different number is assigned to a wider smile, and a separate number is for whatever the eyes are doing.