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.
Read MoreAmazon’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?
Read MoreThe trap that some voice UIs fall into is that you pretend the users are talking to HAL 9000 when actually, you've just built a better IVR, and have no idea how to get from the IVR to HAL. How can we find the mental models for this to work - to bring less rather than more friction?
Read MoreWith Amazon's Echo, Snapchat Spectacles or the Apple Watch, we're unbundling not just components but apps, and especially pieces of apps. We take an input or an output from an app on a phone and move it to a new context. We remove friction, but we also remove choices.
Read MoreChat bots tap into two very current preoccupations. On one hand, the hope that they can actually work is a reflection of the ongoing explosion of AI, and on the other, they offer a way to reach users without having to get them to install an app.
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