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I feel like every recommendation service works this way - YouTube, Amazon, Spotify, etc. Whatever the last thing you looked at becomes your entire life's missio
by beart 4y ago
I feel like every recommendation service works this way - YouTube, Amazon, Spotify, etc. Whatever the last thing you looked at becomes your entire life's mission according to these systems. When I think about all the buzz words around machine learning, ai, and so on, it's completely incompatible with the reality I see. What exactly are all these engineering teams doing just to end up with this result?
Amazon might be the worst example though. Buy something like a bike rack for your vehicle and Amazon will recommend nothing but other bike racks... as though I need dozens of them for one car.
- Arrath 4y agoAmazon really, really likes to recommend me a wide variety of shower curtains after buying one, 4 years ago. Give it a rest already.
- HeckFeck 4y ago> Buy something like a bike rack for your vehicle and Amazon will recommend nothing but other bike racks... as though I need dozens Perhaps they beta tested only with Jeff Bezos who had this exact quandary.
- hombre_fatal 4y agoYoutube does have a great escape latch though: go to the History tab and delete your viewing history. Your recommendations start from scratch and you’ll get funneled into a potentially new corner of videos. With that in mind, I think Youtube recommendations are quite good. Just do it when your recommendations get stale, monthly or so. I wish other platforms had that like Amazon.
- joe_guy 4y agoAmazon actually has a pretty detailed page that lets you control what feeds back into your recommendations. https://www.amazon.com/gp/yourstore/iyr/ https://www.amazon.com/gp/yourstore/iyr/
- hombre_fatal 4y agoThanks, I had no idea. This is great.
- piva00 4y agoIt'd be great if I didn't use my History to actually find videos I've previously watched... I don't understand why recommendation engines just don't provide a reset button. It'd be better for everyone involved: content provider, content creators, users, ad buyers.
- JohnFen 4y ago> With that in mind, I think Youtube recommendations are quite good. Having to nuke a valuable reference like your history in order make the recommendations approach something useful is the opposite of "quite good".
- hombre_fatal 4y agoWell, I'm one to appreciate what we have available to us especially compared to the alternatives and temper my appreciation accordingly. I don't know if I use a single service that gives me particularly compelling control over recommendations. Though I also don't find myself deep-diving my history so often that clearing it every few months affects my life, but I suppose I can see how that could be a setback.
- JohnFen 4y agoMy main point is that if the recommendations are improved by giving YouTube _less_ information to work with, that's a solid sign that the recommendation system is borked.
- jdgoesmarching 4y agoUnfortunately Tiktok is the only platform that nails it for me. It regularly manages to find old hobbies or interests back into the rotation, Youtube’s recommendations are just matching my most recent searches while occasionally throwing in Nazi crap I never asked for.
- deleted 4y ago[deleted]
- mattbrewsbytes 4y agoIt appears to any end user that knows some basic logic and looping concepts that the advanced AI/ML/whatever recommendation engine is no better than looping over the list of recent content (videos, products, etc.) and selecting more content that has same keywords. If you remove the volume and distributed systems elements for large systems its probably a single SQL query joining 2 tables, history and products (or videos or whatever). For the bike rack example, to make it "smarter" you could have a product type that is something like "one-time purchase" and have a linked product type that is accessories for the one-time product, like helmets, pumps, tire changing kits, inner tubes, water bottles, etc. This would be what a retail worker at a bike shop would do - ask if you need any accessories, maybe point out clearance/sale items. Thats it, no fancy engines/AI/ML needed. If the customer wants other stuff, there is a search bar they will likely use. I chalk it up to Resume Driven Development and just the innate tendency of engineers over-engineering things because that's how our brains work.