Technology as Heirloom

Source: Fast Company, Jan 2014

Olsson has hired like-minded designers, who believe that technology should be crafted more like an ageless heirloom, an object we hold dear.

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Nest: Physical Graph

Source: Mashable, Jan 2014

Google hasn’t said anything more than a few vague statements about what it plans to do with Nest, but the acquisition is the company’s beachhead into “Internet of Things,” probably more accurately described in this context as the physical graph.

You’ve probably heard of the knowledge graph (what you know), the social graph (who you’re friends with) and the interest graph (what you like to do), and the power that data has in aggregate. Google and others have deep hooks into all of those spaces but so far no one has made much headway into the physical graph, the pattern that emerges from the movements of individuals and how they interact with physical systems.

“The data is the interesting part in all this,” says Thorsten Kramp, who develops Internet of Things technologies for IBM. “An individual device by itself is not so interesting. If you start collating data from different sources, this is big analytics. This is where the value comes in.”

unlocking the physical graph could do even more. By knowing how vast numbers of people move, Google will start to decipher patterns. It already does this with every other piece of software, identifying trends, surfacing popular apps and analyzing crash reports to improve its products. Knowing how people live will take the idea even further, providing insight to Google and others on how to offer the best products and when.

The full picture of Tony Fadell’s conscious home is probably a decade away at least

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Google Acquires Nest for $3.2 Billion

Source:  NYTimes, Jan 2014

Google and Nest: Two Companies in the Business of Understanding You

Rather than thermostats, Nest’s key technologies were described by Mr. Fadell in an interview last November as “communications, algorithms, sensors and user experience, running over a network to the cloud.”

Nest is interested in how people behave inside their houses; the thermostat was just the first step to understanding that. Its sensors gave information about interactions; after that, algorithms on everything from user preferences to battery power were deployed to give people a sense of control they had not had before. As Mr. Fadell put it at the time, “we’re focused on experience.”

Google also has about $56.5 billion in cash, so Nest isn’t that much of a drain. Pile it up too much, in fact, and the shareholders may start asking for it back. Better to spend on perhaps the most valuable asset of our time: a better understanding of human behavior, in all its forms.

Related reading: NYTimes, Nov 2013

The key technologies are communications, algorithms, sensors and user experience, running over a network to the cloud. You have to go top to bottom, with knowledge not just of design, but of the device, the network, the data services, and back down to the sensors — and the battery life implications of all that. You need to have expertise at every one of those levels. Then we do a lot of analytics on products, sales and customer support.

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Visual Search for the Visual Web

Source: Read Write Web, Jan 2014,

Modern search engines have been developed to identify textual keywords, so the concept of search by image is a major paradigm shift. Even Google relies on adjacent text content in order to identify images (and reverse image search just matches like pixels). 

For a while, Pinterest’s internal search engine was dependent on textual cues like alt text, words in the image link, and the user’s image description, to identify photos. 

According to Jing and Liu, Visual Graph combines big data elements with detailed individual image analysis, or as their latest post says, “Our approach is to combine the state-of-the-art machine vision tools, such as object recognition (e.g. shoes, faces), with large-scale distributed search and machine learning infrastructures.”

Pinterest is already the Visual Web’s most notable search engine—just not a very good one. So far, it relies too much on textual and user created context. But this latest acquisition indicates Pinterest’s eagerness to change that. 

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Buffer’s Open Salaries

Source: Buffer website, Dec 2013

The salary formula

Salary = job type X seniority X experience + location (+ $10K if salary choice)

  • job type = base
  • happiness hero = $45,000
  • content crafter = $50,000
  • engineer = $60,000
  • designer = $60,000
  • Operations officer base = $70,000
  • Executive officer base = $75,000
  • seniority = base multiplier
  • Senior + 5% base and 3k/$m revenue
  • Lead +7% base and 4k/$m revenue
  • VP + 10% and 6k/$m revenue
  • C-level +20% and 8k/$m revenue
  • COO +20% and 10k/$m revenue
  • CEO + 20% and 12k/$m revenue
  • experience = multiplier
  • Master: 1.3X
  • Advanced: 1.2X
  • Intermediate: 1.1X
  • Junior: 1X
  • location = additional
  • A: +$22K (e.g. San Francisco, Hong Kong, Sydney, London, Paris, New York)
  • B: +$12K (e.g. Nashville, Birmingham, Vienna, Austin, Vegas, Tel Aviv)
  • C: +$6K (e.g. Talinn, Warsaw, Bucharest, Santiago)
  • D: +$0K (e.g. Manila, Delhi, Hanoi)
  • equity / salary choice
  • you get a choice of more equity or more salary, if you choose salary, you get +$10K
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Current AR focuses upon Actual Reality

Source: TechCrunch, Nov 2013

… essentially with Junaio Mirage – which is really a prototype right now – when you put on Google Glass or other wearable devices you can see any of the content of Junaio in your real environment.

This will lead to this “always on, always augmented” theme again because content is the key. If you don’t have the content, what will the glass see?

… a new way of picking up information about real-world objects.

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Wearables to Improve Sports Coaching

Source: Forbes, Nov 2013

In a sport where speed and aggression rule, instantaneous understanding of what’s taking place on the field literally changes the game. What’s more, real-time data turns the concept of practice and training on its head. Coaches no longer have to rely only on hindsight to guide the team. Players can immediately see why a certain play didn’t work—or did. In this video, head coach Julian Nagelsmann explains how he uses the data to monitor reaction times and aggressiveness, guiding players to make adjustments for peak performance long before they arrive at game day as a professional.

… coaches have tested Google Glass to check the exact speed of individual players as they move.

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