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Netflix’s Secret Special Algorithm Is a Human

newyorker.com

41–50 of 62 posts

Re: Netflix’s Secret Special Algorithm Is a Human

#41
I also rather trust the algorithm to see what is a good movie and what is not. In my case the collected ratings of the experts, not the users. Current example: http://cannes-rurban.rhcloud.com/Sundance2015

There are some outliers, typical "festival hits", which only relate to festival specialists, but they are easily detectable, with a "10%" human bullshit detector. Like last years Godard at Cannes, 2012 Leos Carax, 2011 the Kaurismaki and 2010 both the Godard and the Jury winner Weerasethakul. Those outliers are even statistically detectable.

One thing is clear, you can trust the collected experts more than the juries. So I can fully confirm the story.

Re: Netflix’s Secret Special Algorithm Is a Human

#42
It always amazes me how the people in the content creation industries keep their jobs. Even though comprehensive studies have shown that the public responds randomly to entertainment products, they still skate by claiming to 'know what the public wants.' Analysis of the decisions of past executives at movie companies showed that executives who were said to be "on a hot streak" were mostly benefitting from the results of projects started by their predecessors, and then when their "streak" ended and they left, their replacement got the same benefit from the projects they left in the pipeline.

The book 'A Drunkard's Walk' analyses various different industries and situations and shows where randomness shows up. The success of media is one of the strongest ones. No factor correllates with success. Not budget, star-power, genre, directors, nothing. For every runaway hit there are exactly as many abyssmal failures. Before Titanic hit theaters, film critics and industry insiders were dead certain that it would prove to be the most monumental theatrical failure in history, making Kevin Costner's Waterworld look like a walk in the park. Of course, they were wrong. They will always be wrong as often as they are correct. Their entire careers are built on, quite literally, absolutely nothing. These executives choose what gets produced, and they are incompetent at it. Yet they are paid millions of dollars. It's astonishing that they get so far with unmitigated bullshit.

This is why large movie production houses will die. Their performance has always been random in terms of producing successful content. But they always made up for it by having total control of the distribution. Now, distribution is worthless. Any 12 year old with an Internet connection can distribute media better than large corporations can. Take away that control and profit from distribution, and those companies will end up simply fading into bankruptcy after enough failed projects pile up.

Re: Netflix’s Secret Special Algorithm Is a Human

#43
post #41

I also rather trust the algorithm to see what is a good movie and what is not. In my case the collected ratings of the experts, not the users. Current example: http://cannes-rurban.rhcloud.com/Sundance2015 There are some outliers, typical "festival hits", which only relate to festival specialists, but they are easily detectable, with a "10%" human bullshit detector. Like last years Godard at Cannes, 2012 Leos Carax,…

Rotten Tomatoes' rating, mentioned in the article as scoring THE BRONZE as 10% (though the RT now says 18%), is also a collection of professional reviewers' ratings.

Re: Netflix’s Secret Special Algorithm Is a Human

#44

It always amazes me how the people in the content creation industries keep their jobs. Even though comprehensive studies have shown that the public responds randomly to entertainment products, they still skate by claiming to 'know what the public wants.' Analysis of the decisions of past executives at movie companies showed that executives who were said to be "on a hot streak" were mostly benefitting from the results…

You might also be interested in Duncan Watts' book "Everything is Obvious", which explores this tendency we have to assume that observed success equates to some skill. Its a nice read.

Re: Netflix’s Secret Special Algorithm Is a Human

#45
post #39
post #30

Earlier quoted context omitted.

I think it does need to scale. What happens when after a bus event? Someone else has to watch every film in existence? It is not enough to just watch the new films - you have to have a memory of all other films in order to make that association.

> Someone else has to watch every film in existence? To some extent, all the film program students and film critics provide your backup reserves: they're watching tons of films on their own, and you don't even have to pay them until you hire them.

> VidArc was a tiny store in a mini-mall, with barely room to squeeze past other customers, but it made up for its size with the percentage of rare and obscure titles that were available, and with the knowledge of the film-nut staff, notably the cinema-obsessed and mile-a-minute talker Quentin, whose low-budget life at the time has been explored in several books. Denise's card was number 1410, and when I made my trek from Oregon in the Orange Monster (my '72 Olds Cutlass), I became a customer as well, discovering the world of strange and disturbing cinema under the tutelage of Quentin, Rowland Wafford, Gerald "Big Jerry" Martinez, Stevo Polyi, Roger Avary, and the owner of VidArc, Lance Lawson.

http://toddmecklem.com/quentin.html

Re: Netflix’s Secret Special Algorithm Is a Human

#46

Hollywood Video's corporate office had a guy, one guy whose job it was to just watch movies. He'd watch them, make sure it was categorized properly, then create associations with other movies that "you might like" if you like this movie, and vice versa. All kept in a spreadsheet that we later plugged in. We also thought there should be an algorithm, but he was pretty dang good at what he did.

Very interesting. Did he enjoy it or did he get bored? Did he have to watch some horrific films? Did he feel like his brain was being polluted as more degenerate films come out? Did it affect his perception of reality?

Just interested.

Re: Netflix’s Secret Special Algorithm Is a Human

#47

See also Shazam's Secret > The hunt keeps Mr. Slomovitz on his toes. Every morning, he skims dozens of music blogs, checking for new releases he might have missed, as well as the iTunes, Amazon.com and Billboard charts, and blog aggregators like the Hype Machine. Most weeks he also goes to local record stores to see if there is something in stock he has not heard of, or if older albums are being remastered or reissue…

Shazam actually has 2000 music geeks in a call center who listen to tiny audio fragments and guess which song it is. The algorithm just makes sure the rock geek gets the rock songs, and so on.

Re: Netflix’s Secret Special Algorithm Is a Human

#48
post #12

> featuring the television star Melissa Raunch Whoa there! It's Rauch. Kind of a Freudian slip there, considering the actress is being named in relation to a sex scene.

Here's another: > Television studios have Nielson ratings It's "Nielsen".

Looks like they've fixed it. But seriously don't they have editors reading this stuff before it goes live?

Re: Netflix’s Secret Special Algorithm Is a Human

#49

As much as people (especially here) think that everything can be solved by Big Data/Machine Learning, human experience and intuition are still very important. No, you can't A/B test your new logo, or the design of your page from scratch. Big Data can't tell you your product sucks. Option A may be better than Option B but this is in the context of both options (and not considering all other possibilities) I see compan…

Those companies are just cargo-culting into the Big Data cult, like everyone else. It doesn't mean they aren't getting useful answers from their black box.

Heck, sometimes it's even useful to have a Magic 8 ball make a decision for me.

Re: Netflix’s Secret Special Algorithm Is a Human

#50
The title is completely misleading, seems like it's talking to the recommendation feature on Netflix, but it isn't. Everyone with common sense knows that big executive decisions aren't made solely by computers, yet the author seems amazed that big executive decisions are ultimately made by big executives. Talk about clickbait, huh?
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