Why Netflix Has Never Envied the Success of Google or Facebook

Netflix is a major player in the so-called "big data" game, as the success of programs like House of Cards demonstrates, but they don't envy larger companies like Google or Facebook for one simple reason.

Todd Yellin:  So it's funny, big data has been kind of a cliché in Silicon Valley for the last few years: big data this, big data that. Big data is really one big mountain of garbage with little gems buried it in this tremendous trash heap, and you want to find those gems — you really want to find out what's going to make the experience better. So there are a lot of sophisticated machine learning algorithms that Netflix and other companies deploy to really figure out what are the gems that are going to make a better experience, and what's the rubbish that you want to separate out and push to the side? Once you find those gems, it doesn't make it a more alienated, machine experience — it actually makes it a more personal experience. It becomes much more about the individual member.

When I first got to Netflix we were looking at other companies that were doing personalization and leveraging the kinds of data they couldn't learn from. And one company that obviously wasn't competitive with Netflix was also doing some interesting things was Pandora, the music company. And Netflix is in Silicon Valley and they're up in Oakland, not too far away, and we're down in the South Bay. So we went up to - we had a meeting, a little powwow, this was many years ago, with Pandora. And they were really small then and Netflix was much smaller and we were just comparing notes. What was interesting about Pandora is Pandora had the Music Genome Project where they were tearing apart and deconstructing lots of music on all these different dimensions and trying to really understand the music. And I remember back in these days, and this was like ten years ago, they had their walls lined with CDs all over and they had a whole line of people in this cramped office with headphones on and they were listening to music with this big spreadsheet open and tagging everything about it. 

At that's time at Netflix we were all about rating our titles on a one to five star system and we were very much using a lot of behavioral - a lot of algorithms around the behaviors of what users were doing and based on a lot of clustering techniques. We weren't really deconstructing the titles yet, we would get to that soon after — they weren't really deploying a lot of the collaborating filtering models that we were using on our algorithms. So we compared notes and we influenced each other and we only met a couple of times with them and were paying attention to what other companies were doing in terms of personalization. And based on these learnings, everyone kind of evolved across, it's not just Netflix, other companies that are trying to leverage big data to make it much easier to find something great to watch, great to listen to, great to read, great to buy, and figure out how to use, when to use human created data, a lot of metadata, a lot of deconstructing of what the material is people are watching or listening to or reading and so forth and how to use a lot of behavioral clustering data, what kinds of people are watching these kinds of shows and movies? What kinds of people are watching these or listening to these and so forth?

So it wasn't just Netflix, it's just we are very monomaniacally focused at Netflix and we really want to create great content and we want to get that great content to the right people at the right time. And so that's why we're using the data. Let me throw in one more thing. There are a lot of great companies deploying a lot of interesting techniques, not only in Northern California but around the world. And so right up the road from Netflix you have companies like Google and Facebook and they can be great partners for Netflix at times and there are brilliant people working there, but I don't envy their jobs because their jobs are different than what myself and my team have to do. When we have all this data we have one purpose for this data and that's to make each individual member's experience better. There are no advertisers. We're only subscription. And in a subscription model you use everything you can and you're basically on your knees and you saying please stay with Netflix. Stay another month. It's a great experience. There's lots of great stuff to watch. Here's another great TV show or movie.

But if you're at a Google or a Facebook you're doing really interesting work but you serving two masters: you're serving the consumer and you're serving the advertiser. So when you getting all that big data you're constantly in this conflict of, "do I use this big data to serve the advertiser and put the right advertising front of the right customer to get them to buy something that they didn't sincerely come to the service for, or am I serving the customer showing them the right thing in their newsfeed, showing them the perfect search result and so forth?" So they're very, you know, they're incredible tools in the modern age, whether on using Google Search or using the Facebook newsfeed, but once again, they're even at a more perplexing challenge, we just use the data to serve each individual member.

According to Netflix's VP of Product Development, there's a misconception about big data. It's not a treasure trove of information, as many people and their companies assume, but more like "a big mountain of garbage." The problem, as Todd Yellin sees it, is sifting through the data to find the information that will actually benefit users, and that data is few and far between.


Yellin appreciates the simplicity of the subscription model on which Netflix depends. While making the on-demand entertainment company entirely beholden to their customers for success, unlike Google and Facebook which draw substantial revenue from advertisers, it simplifies their understanding of big data. Ultimately it means serving one master, the customer, instead of two.

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Image source: Christian Zimmerman/USGS/Big Think
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The Barry Glacier gives its name to Alaska's Barry Arm Fjord, and a new open letter forecasts trouble ahead.

Thanks to global warming, the glacier has been retreating, so far removing two-thirds of its support for a steep mile-long slope, or scarp, containing perhaps 500 million cubic meters of material. (Think the Hoover Dam times several hundred.) The slope has been moving slowly since 1957, but scientists say it's become an avalanche waiting to happen, maybe within the next year, and likely within 20. When it does come crashing down into the fjord, it could set in motion a frightening tsunami overwhelming the fjord's normally peaceful waters .

"It could happen anytime, but the risk just goes way up as this glacier recedes," says hydrologist Anna Liljedahl of Woods Hole, one of the signatories to the letter.

The Barry Arm Fjord

Camping on the fjord's Black Sand Beach

Image source: Matt Zimmerman

The Barry Arm Fjord is a stretch of water between the Harriman Fjord and the Port Wills Fjord, located at the northwest corner of the well-known Prince William Sound. It's a beautiful area, home to a few hundred people supporting the local fishing industry, and it's also a popular destination for tourists — its Black Sand Beach is one of Alaska's most scenic — and cruise ships.

Not Alaska’s first watery rodeo, but likely the biggest

Image source: whrc.org

There have been at least two similar events in the state's recent history, though not on such a massive scale. On July 9, 1958, an earthquake nearby caused 40 million cubic yards of rock to suddenly slide 2,000 feet down into Lituya Bay, producing a tsunami whose peak waves reportedly reached 1,720 feet in height. By the time the wall of water reached the mouth of the bay, it was still 75 feet high. At Taan Fjord in 2015, a landslide caused a tsunami that crested at 600 feet. Both of these events thankfully occurred in sparsely populated areas, so few fatalities occurred.

The Barry Arm event will be larger than either of these by far.

"This is an enormous slope — the mass that could fail weighs over a billion tonnes," said geologist Dave Petley, speaking to Earther. "The internal structure of that rock mass, which will determine whether it collapses, is very complex. At the moment we don't know enough about it to be able to forecast its future behavior."

Outside of Alaska, on the west coast of Greenland, a landslide-produced tsunami towered 300 feet high, obliterating a fishing village in its path.

What the letter predicts for Barry Arm Fjord

Moving slowly at first...

Image source: whrc.org

"The effects would be especially severe near where the landslide enters the water at the head of Barry Arm. Additionally, areas of shallow water, or low-lying land near the shore, would be in danger even further from the source. A minor failure may not produce significant impacts beyond the inner parts of the fiord, while a complete failure could be destructive throughout Barry Arm, Harriman Fiord, and parts of Port Wells. Our initial results show complex impacts further from the landslide than Barry Arm, with over 30 foot waves in some distant bays, including Whittier."

The discovery of the impeding landslide began with an observation by the sister of geologist Hig Higman of Ground Truth, an organization in Seldovia, Alaska. Artist Valisa Higman was vacationing in the area and sent her brother some photos of worrying fractures she noticed in the slope, taken while she was on a boat cruising the fjord.

Higman confirmed his sister's hunch via available satellite imagery and, digging deeper, found that between 2009 and 2015 the slope had moved 600 feet downhill, leaving a prominent scar.

Ohio State's Chunli Dai unearthed a connection between the movement and the receding of the Barry Glacier. Comparison of the Barry Arm slope with other similar areas, combined with computer modeling of the possible resulting tsunamis, led to the publication of the group's letter.

While the full group of signatories from 14 organizations and institutions has only been working on the situation for a month, the implications were immediately clear. The signers include experts from Ohio State University, the University of Southern California, and the Anchorage and Fairbanks campuses of the University of Alaska.

Once informed of the open letter's contents, the Alaska's Department of Natural Resources immediately released a warning that "an increasingly likely landslide could generate a wave with devastating effects on fishermen and recreationalists."

How do you prepare for something like this?

Image source: whrc.org

The obvious question is what can be done to prepare for the landslide and tsunami? For one thing, there's more to understand about the upcoming event, and the researchers lay out their plan in the letter:

"To inform and refine hazard mitigation efforts, we would like to pursue several lines of investigation: Detect changes in the slope that might forewarn of a landslide, better understand what could trigger a landslide, and refine tsunami model projections. By mapping the landslide and nearby terrain, both above and below sea level, we can more accurately determine the basic physical dimensions of the landslide. This can be paired with GPS and seismic measurements made over time to see how the slope responds to changes in the glacier and to events like rainstorms and earthquakes. Field and satellite data can support near-real time hazard monitoring, while computer models of landslide and tsunami scenarios can help identify specific places that are most at risk."

In the letter, the authors reached out to those living in and visiting the area, asking, "What specific questions are most important to you?" and "What could be done to reduce the danger to people who want to visit or work in Barry Arm?" They also invited locals to let them know about any changes, including even small rock-falls and landslides.

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