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However, a lot of usecases are time insensitive rankings. Like recommending content on netflix, spotify etc. (spotifys discover weekly even has a one week! request time :D).
In which case you can just run your ranking and store the recs in your DB and its much much easier.
Is there any recommendation system people we actually happy with? They all seem to suck in my experience
Off-topic, but how did Netflix manage to get itself inserted into the FAANG acronym anyway? Their impact on the tech industry is trivial compared to all the others. Sure, if you just take out the N it's offensive, but we could have said "GAFA" or "FAAMG" would be more accurate to include Microsoft in their place.
All the cool kids say GAMMA now.
I’ve built one of these at FAANG. Generally the different parts of the system are completely separate teams that interact through apis and ingest systems. Usually there’s a mix of online and offline calculations, where features are stored in a nosqldb and some simple model runs in a tomcat server at inference time, or the offline result is just retrieved. Almost everything is precomputed. We had an api layer where an…
Earlier quoted context omitted.
Netflix has contributed a lot to Java micro services, see Eureka and Hystrix.
as well as to ML - Netflix Prize ( https://en.wikipedia.org/wiki/Netflix_Prize ) and Metaflow ( https://github.com/Netflix/metaflow )
But for every other one of the FAA(N)G companies, I can barely work a day as a developer without touching every one of their technologies. Yeah, Netflix got into ML years before most, but the netflix prize exists as a distant cautionary memory, and as an ML professional, I'd literally never heard of metaflow before. Just sayin'.
Off-topic, but how did Netflix manage to get itself inserted into the FAANG acronym anyway? Their impact on the tech industry is trivial compared to all the others. Sure, if you just take out the N it's offensive, but we could have said "GAFA" or "FAAMG" would be more accurate to include Microsoft in their place.
All I know is that Facebook's recommendation systems always show me things that I hate to see. I suppose they may "work" at scale, but at an individual level it's epic failure.
FB needs an Ad-Rev-Share-Model with ALL of its users... Imagine if FB were to pay a fraction% of how yur data was used and paid you for it... It may be a small amount, but in super 4th world countries, it could affect change in their lives... Now imagine that this becomes big... and it works well. Now imagine that the populous is aware of the hand of god above them just pressing keys to affect land masses (yes I am r…
Off-topic, but how did Netflix manage to get itself inserted into the FAANG acronym anyway? Their impact on the tech industry is trivial compared to all the others. Sure, if you just take out the N it's offensive, but we could have said "GAFA" or "FAAMG" would be more accurate to include Microsoft in their place.
FAANG was created by the TV personality Jim Cramer to talk about high growth tech stocks. At the time Netflix was doubling every year. It was based purely on finance. It's now been taken over by the tech industry to be shorthand for places that are highly selective in their hiring and tend to work on cutting edge tech at scale. That being said, the impact of Netflix on tech is pretty big. They pioneered using the clo…
Which is to say they were AWS's biggest early customer? Doesn't really seem like Netflix should get the credit for that one.
Off-topic, but how did Netflix manage to get itself inserted into the FAANG acronym anyway? Their impact on the tech industry is trivial compared to all the others. Sure, if you just take out the N it's offensive, but we could have said "GAFA" or "FAAMG" would be more accurate to include Microsoft in their place.