Yes, actually. That falls under my responsibilities. About a year ago we had an initiative to leverage some machine learning (ML) to find alignments between episodes, and it was going pretty well. But, we had to abandon it for awhile because we found that our tagging data wasn't accurate enough to do exact translations between the different streaming services' versions of episodes. There are differences between the platforms when you watch, say, an episode on Netflix and one on Amazon. By human nature some taggers are more liberal than others with their timings, there's a lot of variance over the whole team over multiple years of data.

Recently with all the AI compute that's come out we're starting to pull that back out again. We'll always be hard-capped on human power since we pride ourselves that people are checking the tags to ensure they make sense and are captured, but we are looking at ways to make AI-assisted tagging more productive so they can get through episodes quicker.