I meant something akin to recommendation engines like TikTok’s, applied to generative models instead of user-generated content.

Start-off with generic, "one size fits all", generated content, using a few parameters such as rough area, time of day, time of the wear, what’s currently popular at that time in that area, what’s popular with the person who created the link if they got in through that, etc.

Then, use the player’s actions (playtime, engagement, sharing, whatever) to infer preferences, and fine-tune the model using both context (time of day, location, other players if multiplayer, etc) and those preferences.

Again, recommendation engine, applied to generative models.

I wouldn’t wager on how distant or close that future will be.

I don’t think it’s doable today, but it’s so obvious that I am certain people are currently working on it. And perhaps some duct tape (sorry, heuristics and expert systems) may be able to somewhat fill the gap in current or near-future models’ capabilities.

But I’m certain (unless copyright laws end up killing such use cases), that it’s the future for both streaming platforms (Netflix, Disney, Spotify & all), content-driven "social" media platforms (TikTok, YouTube, Instagram,…), and video games. Most of them anyway. Some might doubt it can rival with the greatest movies, books, or games, but it doesn’t need to. It just needs to be as good as the cheap filler content these platforms are mostly filled with.

I just hope we’ll find a way to preserve those industries so we can keep getting great new things.