Inside The Netflix/Comcast Deal and What The Media Is Getting Very Wrong — Streaming Media
Dan Rayburn clarifies some of the bad reporting on the Netflix Comcast deal: “it simply comes down to Netflix making a business decision that it makes sense for them to deliver their content directly to Comcast, instead of through a third party” and adding that Comcast guarantees certain quality by an SLA.
The Plus in Google Plus? It’s Mostly for Google — NYTimes
Even if Plus isn’t where you spend your time, it’s the basis for a consolidated view of your activity across Google. That will become even more important with time. “With a single Plus account, the company can build a database of your affinities.”
We’re Leaving — The Bygone BureauI like this take on the discussion of the “post-verbal” in Her as suggesting a time when data supplants language. It was a very brief moment in the movie, but I think it’s at the crux of how we will relate to our machines going forward.
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If you read me regularly, you know I am a fan of programmatic adtech. In fact, I think it’s one of the most important developments of the 21st century. And over the past few quarters, adtech has gotten quite hot, thanks to the recent successes of Rocket Fuel (up to 50 and holding from its open at 29), Criteo (trading above its already inflated opening price of 31), and, by extension, Facebook and Twitter (don’t get me started, but both these companies should be understood as programmatic plays, in my opinion).
But while I like all those companies, I find Rubicon’s recent filing far more interesting. Why? Well, here’s the money shot of the S-1:
Read MoreIndependence. We believe our independent market position enables us to better serve buyers and sellers because we are not burdened with any structural conflicts arising from owning and operating digital media properties while offering advertising purchasing solutions to buyers.
(image) If you weren’t under a rock yesterday, you know Facebook turned ten years old this week (that’s a link to a Zuckerberg interview on the Today Show, so yep, hard to miss). My favorite post on the matter (besides Sara’s musings here and here – she was at Harvard with Zuck when the service launched) is from former Facebook employee Blake Ross, who penned a beauty about the “Rules” that have fallen over the past ten years. Re/code covers it here, and emphasizes how much has changed in ten years – what was once sacred is now mundane. To wit:
– No, you can’t let moms join Facebook because Facebook is for students.
– No, you can’t put ads in newsfeed because newsfeed is sacred.
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This week, lots of talk of data ethics and infopolitics. As always, if you want to keep up with what we’re reading/thinking about on a weekly basis, the best way is to subscribe to the “else” feed, either as an email newsletter or through RSS. And tweet us links!
Google Beat Facebook for DeepMind, Creates Ethics Board — The Information
DeepMind acquisition terms required that Google establish an artificial intelligence ethics board.
When No One Is Just a Face in the Crowd — NYTimes
Whether tracking potential shoplifters or big spenders, commercial facial recognition in the physical world using “Faceprints” is becoming a reality.
Is the public ready to accept the infinite glance of our own technology? That question springs up nearly everywhere I look these days, from the land rush in “deep learning” and AI companies (here, here, here) to the cultural stir that accompanied Spike Jonze’ Her. The relentless flow of Snowden NSA revelations, commercial data breaches, and our culture’s ongoing battle over personal data further frame the question.
But no single development made me sit up and ponder as much as the recent news that Google’s using neural networks to decode images of street addresses. On its face, the story isn’t that big a deal: Through its Street View program, Google collects a vast set of images, including pictures of actual addresses. This address data is very useful to Google, as the piece notes: “The company uses the images to read house numbers and match them to their geolocation. This physically locates the position of each building in its database.”
In the past, Google has used teams of humans to “read” its street address images – in essence, to render images into actionable data. But using neural network technology, the company has trained computers to extract that data automatically – and with a level of accuracy that meets or beats human operators.Not to mention, it’s a hell of a lot faster, cheaper, and scaleable.
Read MoreGartner Says by 2017, Mobile Users Will Provide Personalized Data Streams to More Than 100 Apps and Services Every Day — Gartner
Gartner offers some estimates on apps, wearables, internet of things, and other interfaces that are becoming data.
OfficeMax Blames Data Broker For ‘Daughter Killed in Car Crash’ Letter — Forbes
The extent of data brokers’ overreach into the sensitive details of our personal lives is revealed in uncanny misfires such as this.
Nest thermostat acquisition is Google’s home invasion — New Scientist
Google’s $3.2B acquisition of Nest is all about staking a claim as the data interface into the home.
How Google Cracked House Number Identification in Street View — MIT Technology Review
Interesting details into the development of the neural network that’s helping to identify distorted street numbers picked up by Street View images.
