[drdaeman]

Yeah, well, I could imagine being an outlier with some service or two - but everywhere? I'm a grumpy ass who loves to nitpick, but I don't think I'm that unique.

Even the Google Ads (which are supposed to have some magic pixie dust algorithms done by the fanciest experts in the field because that's Google's bread and butter) are typically showing me some products I couldn't care less about. It's always some random post somewhere (which could be an ad) that actually makes me interested and drives me to making a purchase, not some bullshit video banner.

> the operators of the system look at the efficiency of the system over larger parts of the population

My guess is that they look at engagement metrics, not consumer happiness or satisfaction. And even though I'm pretty much disappointed, I still use those services and still click on "related products" and even check some book samples etc. - in hope that maybe I'm wrong, and maybe this time it's a good recommendations. Very infrequently that happens, but mostly it's not what I'm interested in. So I go find some non-machine recommendations, search for those and thus remain an active user operators want on their platform.

[hnfong]

I agree most recommendation engines simply suck. (I can't imagine how they spent millions hiring Machine Learning PhDs and end up with that crap)

That said, youtube recommendation algorithms are usually sane. I suspect the depth and breadth of available videos (which are actually potentially interesting) helps, whereas for ads, the platform's primary goal is to shove unwanted stuff down viewer's throats, and if 99.9% of the people don't actually want to see the ads, they still need to pick the ones "most likely" wanting to see them, even if that probability is like 1%.