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It’s one of the most common, low-stakes annoyances of up-to-date life: You plop down on the couch at the end of the day, finally having a few minutes to watch one of the dozens of amazing shows or movies available to you thanks to the era of peak television and the advent of streaming, and you start scrolling. Instead of actually watching anything, you spend an endless evening opening apps, aimlessly scrolling through endless rows of same-looking tiles. Eventually, you give up and watch Office Again.
ON this episode Weather forecastwe take a look at why TV and movie recommendations are so complicated and whether AI can improve them. If Spotify can create endless playlists of music you’ll like, and YouTube and TikTok always seem to have something perfect ready to go, why can’t Netflix, Hulu, or Max do it right?
It turns out that AI can assist, at least a little bit. Because models from OpenAI, Google, and others have absorbed so much information about movies and shows—not just their titles and genres, but all the synopses, reviews, summaries, and more from across the web—they can synthesize that information and find connections between titles that were previously demanding to find. And as context windows get bigger, these models can actually absorb and understand an entire movie at once, opening up entirely fresh ways to understand them.
Ultimately, though, recommendations are a human problem. Because we’re all human. What you want to watch and why you like what you like is far more convoluted—and far more nuanced—than even the best models can understand. As a result, the idea of sitting down, opening Netflix, and having exactly the right title pop into your head right away isn’t going to happen anytime soon. So instead of hoping for the best, we’re exploring ways to exploit AI tools right now to get to content at least a little faster. Because watching movies is great; skipping through too many of them is seriously overrated.
If you want to learn more about what we cover in this episode, here are some links to assist you get started: