12 ms·

While these are amazing performance numbers, I seriously wonder if all this expensive AI magic will be cost effective in the end. Their lead example is recomme

• lhoff 6y ago
  I could imagine thats a bias. That we just remember the bad examples when den recommendation was bad but not when it was good because we didn't make the connection. I'm asking myself that for quite some time. Do you use a tracking blocker. That could also be a reason why you get bad recommendations.
• franklampard 6y ago
  My Spotify recommendation is amazing. I have been an Apple Music user, but I am subscribing to Spotify just for its recommendations.
  • mottosso 6y ago
    Was about to say the same. Have been eagerly awaiting an updated "Discover Weekly" playlist every Monday for years and it keeps getting better.
  • mattnewton 6y ago
    Scrolled through the comments exactly for this. In addition to the discover weekly, I'll often make a new playlist of 5-10 similar songs I like to get another in the same vein, and it works very well for my decidedly not-chart-topping music preferences. Maybe there are some genres I don't listen to enough that it struggles with?
    • semi-extrinsic 6y ago
      Spotify has a couple of weird fetishes. If you throw a Eurovision song or a song in your local language into a playlist with unrelated music, it will exclusively recommend those genres. Even when they are outnumbered 20 to 1 in the playlist in question.
  • walrus01 6y ago
    If I had to guess this is partially because Spotify has actual humans with ears who are categorizing specific artists into genres. Not because of any great advancement in AI. If you like portishead, you might like (similar thing). Just within electronic music, look at how many genres and sub-genres have been categorized by someone simply as a hobby project. Now updated for the web 2.0 era. https://music.ishkur.com/ https://music.ishkur.com/
    • franklampard 6y ago
      One of their ways: https://github.com/spotify/annoy https://github.com/spotify/annoy
    • anjc 6y ago
      > Spotify has actual humans with ears Yeah the actual humans with ears are me and you. They use play-time as the basis for recommendation as well as content-similarity, and put effort into de-biasing this data for, e.g., position bias. This is the same for YouTube etc. Spotify is one of the best examples of a modern large-scale recommender system, for me.
  • guywhocodes 6y ago
    This is so foreign to me that I have have to ask this at the risk of appearing very rude, but from my perspective this question makes total sense. Do you have a memory problem? My weekly have always been 30-70% the same recordings of songs I have already listened to at least ten times. And it's always been this way.
    • franklampard 6y ago
      Yo that’s indeed very rude. Why would you assume I use discover weekly to discover music? I just use the Radio feature, which plays endless amount of songs based on the song you started with.
      • guywhocodes 6y ago
        I'm sorry but I couldn't come up with a nicer way to ask an objective question about it. The radio feature is global to all playback situations so I assumed that couldn't be it.
      • mrmonkeyman 6y ago
        It's not rude. The guy is just curious.
    • Nimitz14 6y ago
      I've been using the weekly for many years now amd that's not the case for me.
    • iambatman 6y ago
      My discover weekly is maybe 50% songs that I've heard before though maybe not on spotify, I think they're from the itunes library I imported.
• powersnail 6y ago
  I've long wondered why recommendations (especially shopping) are so bad. You just bought a light bulb? How about a dozen others? But I've realized that accuracy is not really a problem for them, because a false recommendation at most slightly annoys the user and get glossed over. Among 1000 wrong recommendations, if one works, it's a win (for the company).
  • drusepth 6y ago
    >You just bought a light bulb? How about a dozen others? Ironically, this suggestion is probably driven by real-world behavior. Whether your bulb fails due to age (and you'll probably need replacements for your other similarly-aged bulbs soon), or an electrical problem caused the burn (and you might need another replacement soon), or you just want to stock up, having your exact bulb model recommended also saves you a little time on having to check it yourself. :P I think a lot of "wrong" recommendations are actually right for other users, which seems to be just what you're saying -- they annoy one user but result in more sales for others. From the company's perspective, these recommendation systems are working as expected. On the bright side, that also means in their best interest to improve accuracy (and drive more sales for more users, instead of just annoying them). Hopefully new tools like Nvidia's announcement result in fewer annoying ads.
    • hajile 6y ago
      No matter what I buy, no matter how niche and one-off the purchase is, Amazon never fails to recommend a hundred similar (usually knockoff) products. Instead of focusing on what I just bought, they need to focus on predicting what I'll want to buy next. Just because I bought a coffee maker doesn't mean I'm turning into a coffee maker collector.
• spritecranberry 6y ago
  > Amazon keeps recommending me tampons (I'm a guy) ever since I've had a coworking office with a female colleague in 2015. Men can menstruate too. This statement of yours is harmful because it perpetuates cisnormative stereotypes. Please stick with "I am not a person who menstruates" in the future or something similar.
  • spritecranberry 6y ago
    Your downvoting my remark only shows that HN is still an incredibly unsafe space for people who menstruate and marginalized communities more generally. This is not suprising since HN is white and male.
    • read_if_gay_ 6y ago
      Preach inclusivity and respect, and in the same breath take a cheap out-of-the-blue jab at fucking white males. Truly amazing what it’s come to.
    • p1esk 6y ago
      Here's some perspective: NH is one of the most politically correct online forums in US. US itself is one of the most politically correct and tolerant countries in the world. If you think NH is "incredibly unsafe place" for people who are different (in any respect), try to imagine what would happen to such people in some other cultures (e.g. some Muslim countries, rural Africa/India, etc). I bet an American white male community wouldn't seem so bad. There was zero reason to get offended by the parent comment. If someone did, it's strictly their own personal issue. They should learn how to deal with it and adjust their expectations.
      • barbecue_sauce 6y ago
        What is NH?
        • xdavidliu 6y ago
          News Hacker?
• tehlike 6y ago
  The meme that never dies. There are 1 billion users, each of which spend x$ on the platform. The recommendation system does not need to get 100% accurate (it'd be very hard to get to something that 10% nonaccidental/nonfraud click through rate for example). It needs to be slightly accurate. The difference between 0.5% ctr and 0.6% CTR or conversion is probably 20% increase in revenue, and much more in profits (assuming fixed cost).
  • mrmonkeyman 6y ago
    Then why the billion dollar AI if a simple if-else suffices? Also, how about suggesting products that are actually good. That would raise revenue by 2000%.
  • ogre_codes 6y ago
    This is a perfect example of why end-users shouldn't buy into the idea that all of this invasive tracking is getting them better/ more relevant advertising. That Google and Facebook were able to pedal this lie for so long and so effectively is the biggest scam of modern times.
    • leesalminen 6y ago
      My anecdote is that Facebook got really good at targeting ads at me. Once I actually purchased 4 things from FB ads in a short time, I realized I had to quit. Going on 2 years now FB free!
      • jonplackett 6y ago
        Do you regret those purchases?
        • codefreakxff 6y ago
          Not original poster. Also got ads for things I would definitely like. 100% of them were cheap crap that actually did not work at all. Stopped using Facebook because I got tired of the deceptive ads, lack of accountability, and invasive profiling And, yes, I do think Facebook should take responsibility for the content of their ads and products sold through them. If the New York Times only sold ads for scams, and all their articles were lies, we would no longer trust the New York Times Facebook is like Vegas strip junk ads. It may look nice, but you’re going to have a bad time
• walrus01 6y ago
  > Amazon keeps recommending me tampons (I'm a guy) I bought one toilet seat on Amazon and now it thinks I'm a toilet seat collector. No I'm not going to buy another one any time soon, no matter how many color and size/shape/design variations it presents to me.
  • erulabs 6y ago
    This is exactly the issue with all recommendation systems. It's silly when I look at Amazon and see 15 different cat water trays just because I got one for my cat a month ago - but when it comes to social media the effect is really poisonous. YouTube is a good example: if I listen to something about Roman history it's all Rome all the time - a much better recommendation would be to suggest Greek / Persian history - rather than pigeon-holing me after 1 or 2 videos. I really think I would watch more videos if the recommendations -challenged- what I enjoyed, rather than couching me, but I have to assume that someone has run that experiment and ad revenue went down.
    • tachyonbeam 6y ago
      I have that issue as well with the recommendation algorithm on YouTube. It's similar to the challenge of balancing exploration vs exploitation in reinforcement learning. I think that most people want more exploration/discovery so they don't get bored. More exploration also leads to more learning. It's a win-win for everyone.
    • ashtonkem 6y ago
      I occasionally watch firearms videos, usually Forgotten Weapons, and the recommendations it now gives me are ... interesting. The ads seem to think that I’m either a day trader, or I’m desperate to escape from Fake News.
    • the_french 6y ago
      the yt recommendation algorithm is probably the worst among all the major platforms. It will pigeonhole you into the same 10 videos, which you will never escape. I listen to music on youtube relatively frequently but then it will always go back to the same 10 songs its decided i should listen to, no matter what genres I play.
• ehejsbbejsk 6y ago
  I agree with you. The “gold” rush toward ML does not expand the total wallet size outside of a few niche markets.
• zabardasth 6y ago
  nVidia is on its last legs, honestly. If this is the best they can come up with, forget it. What is the real world application/use case for this GPU? I doubt it would be used for autonomous driving - you could buy some cheap used Tesla P100s and toss them on a rack for a better price point IMO.
  • intpx 6y ago
    wow... uh science? for one.Smaller outfits and research groups that want to do rapidly iterate through modeling and simulation but don't have a datacenter. the A100 is about 11 times more performant than a p100 in HPC benchmarks. You can get a dgx station a100 with 4 A100s in it and run it on mains power and have the equivalent of 44 p100s under your desk (for these applications).
• tomdell 6y ago
  My Spotify recommendations are great. Do you listen to music on it often?
• pluto9 6y ago
  I imagine that's their lead example because recommender systems are familiar, easy to understand in terms of functionality, and they get non-technical business types excited about spending money on new AI toys like the A100. There are far more interesting use cases for hardware like this, but AI researchers don't need to be told about them.
• marcinzm 6y ago
  >For all the data that they collect and all the AI that they pay for, these companies get very little revenue to show for it. Not really, they make a shit ton of money from their recommendations and perform extensive A/B testing to keep track of how much money it makes them. Anecdotes aren't data and large tech companies don't spend money for no reason (especially when they can A/B test the impact trivially). Remember that at their scales even a 0.01% increase in revenue is worth $10+ million per year so they don't need to be perfect to make a shit ton of money. There's a reason ML engineers get paid $1+ million and it's not corporate stupidity.
  • laichzeit0 6y ago
    I doubt it’s A/B testing, more likely some multi-armed bandit algorithm.
    • disgruntledphd2 6y ago
      You typically need both. You'll have some kind of MAB in production, but in order to measure individual incremental impacts, you still need a proper experiment.
• m463 6y ago
  Sounds like those folks should buy A100 80GB and up their game! Seriously though - When amazon is showing me all these recommendations, they are charging someone to show these to me. That means I am not the customer of those recommendations. They make money when I browse and I wonder if they make more money doing that than when I actually purchase. Meanwhile to the people selling - they pay to advertise with amazon, and they pay (via a %) to sell as well.
• drusepth 6y ago
  For anecdote's sake, I: - frequently click through on Facebook ads because they're often SaaS products I'd be interested in (and have found a bunch of cool tools I use now) - think my Spotify suggestions are spot-on. I used to use Google Music which had comparable suggestion qualities at the time, but I feel like Spotify has gotten significantly better at suggestions over the past year-ish. - think YouTube is the shining example of controllable recommendation systems. Looking at my front page right now, I'm interested in all 8 of the videos above the fold, and almost every video below it -- probably a direct result from actively guiding/curating what videos get recommended to me. My "to watch" queue is hundreds of videos long since I almost always add more and more videos until I get the time to sit down and watch a chunk, which usually turns into a positive feedback loop of more good videos getting recommended. All three of the above recommendation systems make me enjoy the related product more than I would without them, and probably also directly lead to more revenue for the company (sales on FB, keeping my Spotify sub, and seeing more YT ads). On the other end of the spectrum, posts on FB and Quora are two examples where recommendation systems seem to make products significantly worse, so I guess it's hit or miss depending on whether what you want out of each product aligns with how the recommendation systems are set up.
  • thejosh 6y ago
    The YouTube recommendations have been onpoint, and I'm a huge fan of it as well. I have found new channels I really enjoy but randomly get some extremely left/right wing US political content, but I just hide it (I'm Australian).
  • zokier 6y ago
    > think YouTube is the shining example of controllable recommendation systems. Youtube is the worst. I have all the time to open videos (and think about it!) in private tab so that my recommendations don't get messed up. And then of course on phone you don't have that luxury so you have to go clean history manually. And now they added two interstitials before you can actually view video in private. Shining example indeed
    • dr_zoidberg 6y ago
• gmadsen 6y ago
  I wouldn't consider that the lead example. More like ML algorithms completely destroyed all benchmarks for computer vision algorithms and changed the direction of research completely.
• sbierwagen 6y ago
  > Spotify and Deezer both suggest the chart hits, regardless of how often I dislike that kind of music. Of course they do. Their real customers, record labels, pay handsomely for that service.
  • speedgoose 6y ago
    I'm not sure about that. The famous Spotify discover weekly playlist suggested a chart hit to me only once since its creation years ago, and I liked it. The release radar playlist may have more chart hits, but this one is not super smart. If you listen to a popular artist you will get all its new songs and shitty remix forever, including its chart hits.
• _the_inflator 6y ago
  > Spotify and Deezer both suggest the chart hits, regardless of how often I dislike that kind of music. That is just part of the game and it is called "machine learning". They get to know you better. ;) Annoying but only part of the game/training.
• RobLach 6y ago
  The true question is whether throwing electricity at your algorithms is cheaper than, for example in the Spotify case, hiring a couple hundred curators to hand pick music for a wide range of segments.
• TaylorAlexander 6y ago
  I mean, I work in robotics. And while algorithmic improvements are certainly needed, I think we could manage to use way more processing power too. Think of the Tesla self driving system - a beefier processing system is a big reason its even possible. And on their backend? Gobs of video data crunched in what must be a huge dataset. I think there’s plenty of room to throw more power at the problem and make traction. At least in robotics.
• weinzierl 6y ago
  > Spotify and Deezer both suggest the chart hits, regardless of how often I dislike that kind of music. "It is difficult to get a man to understand something, when his salary depends on his not understanding it." -- Upton Sinclair In other words the reason might be that there is an incentive to suggest you chart hits. The abilities of the recommendation have probably not much to do with it.