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How useful was the Netflix Prize challenge for Netflix?

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Re: How useful was the Netflix Prize challenge for Netflix?

#71

Post by mathattack »

setr wrote: post #28
Supermancho wrote: post #25

Earlier quoted context omitted.

> At the time, Netflix wasn't super high-tech I will admit that it was interesting to see what algorithms were poised to be cutting edge in media recommendation. The result was rather disappointing to me. Netflix STILL isn't that exciting from anything but a compensation standpoint. The problems at netflix are about programming, while the technical challenges are droll at best.

IMO the recommendations are no good because they fundamentally take the wrong approach — rather than ask the user what they like, they try to guess what you like based on usage (which really doesn't correlate well — I watch a lot of garbage because I can’t find things I like, and I don’t have anything better to do.) And they don’t ask because users don’t provide useful answers. But users don’t provide useful answers,…

You may watch garbage (revealed preferences) but that is more important to them in terms of keeping your attention than your wish list (stated preference).

Re: How useful was the Netflix Prize challenge for Netflix?

#72

Post by loeg »

kens wrote: post #51
BB212 wrote: post #20

I think the discussion misses the most important part: The goal of the Netflix prize wasn't to come up with the best algorithm - it was to make the Netflix brand exciting and legitimate to engineers. At the time, Netflix wasn't super high-tech and I'm sure it was hard for them to get the top talent they needed. It seems silly in retrospect now, but I'm certain the reason this was approved was because they wanted the…

> make the Netflix brand exciting and legitimate to engineers As a serious question, why do people include Netflix in the acronym FAANG, which I see on HN all the time? Is there something special about Netflix? Netflix is around the #14 tech company, so it's strange to see Netflix in there instead of Microsoft. Or is the use of FAANG divorced from its literal meaning?

Netflix pays really well.

Re: How useful was the Netflix Prize challenge for Netflix?

#73

Post by saurik »

derangedHorse wrote: post #59
kens wrote: post #51

Earlier quoted context omitted.

> make the Netflix brand exciting and legitimate to engineers As a serious question, why do people include Netflix in the acronym FAANG, which I see on HN all the time? Is there something special about Netflix? Netflix is around the #14 tech company, so it's strange to see Netflix in there instead of Microsoft. Or is the use of FAANG divorced from its literal meaning?

It's probably included because of the sky-high salaries they offer since FAANG is typically an acronym used to refer to top software companies to work for. From what I've heard from friends, Microsoft typically pays the least out of all the companies that make up the acronym and their technologies are also seen as less trendy than the other companies listed.

I had always heard Apple as the outlier for low salaries, not Microsoft.

https://medium.com/@paysa/tech-salaries-who-pays-more-micros...

Re: How useful was the Netflix Prize challenge for Netflix?

#74

Post by bcrescimanno »

makeitdouble wrote: post #40
rrrrrrrrrrrryan wrote: post #31

Earlier quoted context omitted.

Who's more likely to keep renewing their subscription? The person who uses Netflix to watch a ton of trash that they think is "just ok," or the person who merely watches 1 or 2 things per month that they actually enjoy? I'm certain Netflix ran the numbers, and determined that a high-usage customer is the most valuable.

It's interesting how many corporations don't actually "run the numbers" on what we think are important issues. Basically, internal focus and what the rest of the world cares about are disjointed and corps are often blind to obvious aspects. This can be improved by strong internal diversity, but Netflix doesn't look like a bastion of that (yet?) On "just ok" vs stuff actually enjoyable, "just ok" is fine until there i…

Former Netflix employee (2010-2013) here and, if there's one thing Netflix does as well or better than anyone in the industry, it's running the numbers. In particular, in those days, we had two key metrics that were strongly correlated and we would attempt to drive up: Streaming hours and account retention. Higher usage was strongly correlated with account retention to the point that they were the core of nearly every experiment we did.

Re: How useful was the Netflix Prize challenge for Netflix?

#75

Post by setr »

fouc wrote: post #68
setr wrote: post #57

Earlier quoted context omitted.

I don’t think that’s correct. 1-5 stars is sufficient. The problem is that you need reason to continuously update the values as your preferences update over time (what was once a 5-star is now a 4-star, because that last movie I saw was phenomenal ) What you need is sufficient reason to do so — the values need to actually be useful to you to make updating an act of sanity (unlike now, where it’s purely an act of futi…

Relative rating could also work here, "did you enjoy this movie more than this other movie you recently saw" type of deal.

The problem is data entry for the recommendation algorithm is insufficient incentive to constantly use it (thereby providing “truthful”, or highly-correlated, user ratings). The ratings themselves must be directly beneficial to the user, so that the user provides truthful data for their own benefit, and secondarily for the recommendation algorithm.

That is, I’d like to catalog my own list of watched movies, and their relative ratings, so that I can have a useful system (or a direct relationship to recommendations — eg More Like This), from which Netflix can scrape for their algorithms.

That is, if I’m not honest to myself, the ratings themselves will not be honest, and not properly reflect my taste.

Specifically, there must be reason to provide negative ratings in addition to positive, to capture user taste.

Re: How useful was the Netflix Prize challenge for Netflix?

#76

Post by markzzerella »

kens wrote: post #51
BB212 wrote: post #20

I think the discussion misses the most important part: The goal of the Netflix prize wasn't to come up with the best algorithm - it was to make the Netflix brand exciting and legitimate to engineers. At the time, Netflix wasn't super high-tech and I'm sure it was hard for them to get the top talent they needed. It seems silly in retrospect now, but I'm certain the reason this was approved was because they wanted the…

> make the Netflix brand exciting and legitimate to engineers As a serious question, why do people include Netflix in the acronym FAANG, which I see on HN all the time? Is there something special about Netflix? Netflix is around the #14 tech company, so it's strange to see Netflix in there instead of Microsoft. Or is the use of FAANG divorced from its literal meaning?

Netflix uses(used?) double digit percentages of all internet bandwidth. That's a big player by any metric.

Re: How useful was the Netflix Prize challenge for Netflix?

#77

Post by setr »

mathattack wrote: post #71
setr wrote: post #28

Earlier quoted context omitted.

IMO the recommendations are no good because they fundamentally take the wrong approach — rather than ask the user what they like, they try to guess what you like based on usage (which really doesn't correlate well — I watch a lot of garbage because I can’t find things I like, and I don’t have anything better to do.) And they don’t ask because users don’t provide useful answers. But users don’t provide useful answers,…

You may watch garbage (revealed preferences) but that is more important to them in terms of keeping your attention than your wish list (stated preference).

That’s my point. The algorithm goal is not to find what I’d like, but rather what I’d put up with. They only need to find what I’d like every so often, to keep me on the platform.

It’s correct from Netflix’s perspective, but not from mine.

Re: How useful was the Netflix Prize challenge for Netflix?

#78

Post by sand500 »

derangedHorse wrote: post #59
kens wrote: post #51

Earlier quoted context omitted.

> make the Netflix brand exciting and legitimate to engineers As a serious question, why do people include Netflix in the acronym FAANG, which I see on HN all the time? Is there something special about Netflix? Netflix is around the #14 tech company, so it's strange to see Netflix in there instead of Microsoft. Or is the use of FAANG divorced from its literal meaning?

It's probably included because of the sky-high salaries they offer since FAANG is typically an acronym used to refer to top software companies to work for. From what I've heard from friends, Microsoft typically pays the least out of all the companies that make up the acronym and their technologies are also seen as less trendy than the other companies listed.

MS pays less than Amazon?

Re: How useful was the Netflix Prize challenge for Netflix?

#79

Post by rudasn »

rudyfink wrote: post #67
setr wrote: post #28

Earlier quoted context omitted.

IMO the recommendations are no good because they fundamentally take the wrong approach — rather than ask the user what they like, they try to guess what you like based on usage (which really doesn't correlate well — I watch a lot of garbage because I can’t find things I like, and I don’t have anything better to do.) And they don’t ask because users don’t provide useful answers. But users don’t provide useful answers,…

The recommendation system, historically (i.e., in the long-long ago of spinning disks), was insanely good. But then Netflix moved to streaming and, as a consequence, its own--and generally less good--content. By analogy, Netflix went from being a sci-fi future of having and being able to recommend on the basis of _everything_, to having a handful of good offerings and a huge amount of b-movie-level offerings. My gut…

There was LoveFilm or something like that in the UK circa 2004 that worked like Netflix did (I think they bought them eventually).

The recommendations were pretty good, because I remember we mostly picked what was recommended.

Re: How useful was the Netflix Prize challenge for Netflix?

#80

Post by calderwoodra »

I had the pleasure of working closely with Yehuda (one of the earlier prize winners) at Google where he works on TV and Movie recommendations (Search "what to watch" to see his team's work).

He's extremely intelligent and passionate about this space, and every time we spoke I felt like I was learning something new. You can listen to him give an in depth talk about the Netflix problem and solution here [1].

[1] https://youtu.be/YWMzgCsFIFY

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