Smart home, machine learning and discovery

Smart home today looks a lot like the world of kitchen gadgets a few generations ago - and so does machine learning. We have a bunch of cheap commodity components (DC motors! Cameras! Wifi chips! Voice recognition!) and we’re trying to work out how to bolt them together into things that makes sense. There are lots of experiments - some things will be the toasters or benders of the future, and some will be the electric can-opener.

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Is Alexa working?

Amazon’s Alexa has been a huge, impressive and unexpected achievement. Amazon created a category from scratch and left both the AI leader Google and the device leader Apple scrambling in its wake. It’s now sold 100m units. So far, though, this success is pretty contingent - we do still have to ask what Amazon actually gains from this. What do consumers do with these devices that helps Amazon? What fundamental strategic benefit does it get? Amazon has put an end-point into tens of millions of homes - what does it do with it?

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The internet of things

My grandfather could probably have told you how many electric motors he owned. There was one in the car, one in the fridge, one in his drill and so on. My father, when I was a child, might have struggled to list all the motors he owned (how many, exactly, are in a car?) but could have told you how many devices were in the house that had a chip in. 

Today, I have no idea how many devices I own with a chip, but I could tell you how many have a network connection. And I doubt my children will know that, in their turn.  

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