The happy go lucky Down's people, however, are just what you see of them in media. That's a tiny fraction of the entire population with Down's, which consists of a range of horrible and crippling mental and physical disabilities, in addition to increased risk for diseases like early onset Alzheimers.
Giving a child a life like that feels cruel and heartless to me.
Marketed by who though? Like the article says, there is no main company or companies behind this. Just lots of random products cheap from China being resold.
I wouldn't be surprised if some smart folks in China launched a covert social media campaign to sell this stuff. You don't need much (aside from money and some dedication) to create a fad these days, as long as it's something simple and doesn't require extensive concentration to grasp.
They have been popular with folks that owned 3D printer for a while. It could be something simple like a critical mass of 3D printers being reached. My wife was printing these for fun a few months before it all exploded.
That's curious, because in my opinion YouTube recommendations haven't been any good since 2009. Instead of getting interesting, strange and niche content, I'm bombarded with videos that have >100k views, feature clickbait titles and thumbnails and are generally incredibly low effort content.
Methods that work better for a population as a whole might not work better for a large subset of that population, and might even cause users to stop using features entirely. The lack of transparency in recommendation algorithms combined with the homogenizing effect of distributing low-quality content this way is something I find somewhat depressing.
Precisely. But that might be a local minimum. "Show him boobs and action trailers" is guaranteed to make him stay another 40min.
But perhaps there is a more risky strategy that takes longer to craft and actually delivers hours and hours of content to the user (but needs to fail longer before getting there).
It seems like reinforcement learning would be useful, i.e. at a high level, forming a policy for recommendations would require balancing exploration (experimenting with more risky recommendations) vs. exploitation (showing you recommendations that it knows will likely lead to clicks) and using the click-throughs, time spent watching the video, etc. as reward signals.
Does anyone know whether RL is used for recommendation in practical settings, and if so what is the current state of the art?
Giving a child a life like that feels cruel and heartless to me.