I think that the issue is that it's always assumed that similar things are a better recommendation. The issue is at least for myself and other people I've talked to about that a lot of times we're looking for something different from the last thing. For example if I spend a week listening to vintage surf rock the recommendations that could be given might be 60s pop, or more surf rock. But what actually I wanted was to listen to experimental jazz with a retro funk twist on it. How could they anticipate that? Talk to anyone who's deep into some art form, movies, tv, music, and you'll see recommendations given that maintain vibes more than just similar things.
Ask HN: Why do recommender systems not seem good?
21–30 of 68 posts
Re: Ask HN: Why do recommender systems not seem good?
#22You buy a $1000 scooter from Amazon and then it keeps recommending to you other good scooters for months, even after the return window for the first one is closed. Yeah, you'd expect more from ML at this point. I wonder how much of ML research actually gets utilized in industry.
“Why is Amazon trying to sell me an X? I just bought an X. Idiots!”
Amazon is not an idiot:
> You need two insights here:
> 1) Conditional probability is a mathematical technology that does exist.
> 2) Buying X is not entirely random across the population.
> The ways X is not random vary based on the good [math]. Consider refrigerators.
> You probably buy one every ten years. If I don't know where you are in your refrigerator cycle, my prior estimate should be 2.7e-4 probability of you buying it tomorrow.
> Suppose I know you bought yesterday. In my life on earth, I have realized that buyer's remorse is a thing.
> What's a SWAG for how often a purchase immediately goes wrong? Not right color? Fridge DOA? Shoot I mismeasured my kitchen? Wife just hates it? Call that 2%. If I fix it within a week, then 2% / 7 = 2.9e-3 probability of purchasing a new fridge.
> That's a 10X relative risk.
Source: patio11 (Patrick McKenzie)
Re: Ask HN: Why do recommender systems not seem good?
#23It's weird but tiktok is the only one that seems to do a good job. Seriously. The tiktok recommendation algorithm is so good. And then for ads, instagram seems to be the only one that does a good job. I regularly get ads for things I actually want from instagram, never from any other platform.
Re: Ask HN: Why do recommender systems not seem good?
#24> YouTube seems to have a massive recency bias
This is likely intentional to encourage more content creation. Competing with two decades of content is almost impossible, so they make them compete with just 2 weeks of content.
Re: Ask HN: Why do recommender systems not seem good?
#25You buy a $1000 scooter from Amazon and then it keeps recommending to you other good scooters for months, even after the return window for the first one is closed. Yeah, you'd expect more from ML at this point. I wonder how much of ML research actually gets utilized in industry.
[dead]
Re: Ask HN: Why do recommender systems not seem good?
#26I think it's partly just a reflection of how complex and poorly understood taste is.
Re: Ask HN: Why do recommender systems not seem good?
#27Do you think these are optimized for what YOU want or for what the company wants.
YouTube: Is that recommendation for good content or for the highest value content you will consume?
Netflix: The more you use it, the less they make. There is a perverse incentive to put just enough good content in front of you to stay subscribed but not use it more.
Amazon: They dont give a fuck what you buy, the sellers are now in a race to the bottom and that business pays for it self. AWS makes all the money.
Find the perverse incentive and optimize for that.
Re: Ask HN: Why do recommender systems not seem good?
#28You buy a $1000 scooter from Amazon and then it keeps recommending to you other good scooters for months, even after the return window for the first one is closed. Yeah, you'd expect more from ML at this point. I wonder how much of ML research actually gets utilized in industry.
“Why is Amazon trying to sell me an X? I just bought an X. Idiots!” Amazon is not an idiot: > You need two insights here: > 1) Conditional probability is a mathematical technology that does exist. > 2) Buying X is not entirely random across the population. > The ways X is not random vary based on the good [math]. Consider refrigerators. > You probably buy one every ten years. If I don't know where you are in your ref…
Amazon ARE idiots.
So many people complain about this behavior of recommender systems and here comes Patrick dropping some math and saying: “Well, actually there’s this and this probability for this to happen”.
Don’t piss on me and tell me that it’s raining. Before I make a purchase, especially online, I do my research and make a choice, that’s it.
I’ve never returned anything online and I’ve never needed to buy a second item after buying the first one.
If you insist that your math is right, give me a button I can press so I don’t have to care about your probabilities.
Re: Ask HN: Why do recommender systems not seem good?
#29Mostly conjecture on my part, and an anecdote: for some things, I have very specific and niche tastes that come in the form of things that are difficult to label.
Example: rap music and hiphop. For the most part, I don't enjoy it that much. There are a few things though that will make a track palatable to me (or instantly turn me off despite anything else positive about it):
- Sentimentality or romance in the lyrics
- Backing track or samples that are harmonically interesting
- No egregious sexism, misogyny, glorifying of violence, thug/gangbanger culture, etc
- Beats featuring stereotypical trap hi hats kind of annoy me
The way I assume recommendation systems are traditionally designed does not account for this. It sees me listen to these tracks, and thinks I'll probably like something by similar artists or the same artists. As far as I'm aware, Spotify's recommendation system is not aware of things like tempo, meter, tonality, themes of the lyrics, harmony, etc. and so there's no way it can pick tracks like this out from the crowd.
And why would they bother? Those are all much more technically difficult things to implement than forming correlations between IDs in a database.
Re: Ask HN: Why do recommender systems not seem good?
#30Have you used the tiktok one? It's too good for my liking. It can make weird inferences that no other algo can (this is actually why I deleted tiktok, far too addictively good)