else 2.17: “Drag the future here and see if we want it”

This week looked at convergence in wearables, how we live with technology today and in the near future, and the possibility that reality is just a mathematical model. 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!

 

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.”

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else 2.10: “Information that was never designed for a human to see”

This week, we were thinking about data post-language, reading the tea leaves of algorithms, and wondering how to protect the first principles of the web. 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!

 

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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Step One: Turn The World To Data. Step Two?

housenumbers1Is 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.

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else 8.19: Why We Should Replace the Turing Test

433px-Weakness_of_Turing_test_1.svg

(image) Among many other things (we usually add 20-30 items into our book’s Evernote account each week), this past week we read about developments in brain-computer interfaces, and how connecting smart devices introduces new vulnerabilities. We also read about how policy and ethics questions need to catch up with technology that makes surveillance easier. 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.

 

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