Discovering the Smart Home

Interesting thoughts here.   We are discovering.   After reading this I scanned my Alexa app and there were twenty of so 'smart' things.   There were about half as many in Google Home.  And I am still discovering, while they are still learning.   A few are unoperablefor various  reasons, the most common one is they are not connecting to the home Wifi architecture.    Another is that a device is not owned by the 'right' person, or IOT provider, and is awaiting updates.

Benedict Evans  in Andreesson Horowitz

Smart Home, Machine Learning and Discovery
April 04, 2019 In IoT, Machine Learning

‘Smart home’ today is in the same place as electric things in the home a generation or two ago: everyone will have some of these, but we’re working out which makes sense. Everyone got a toaster or a blender, but no-one got an electric can opener, and smart homes look the same. We’re in discovery mode.

My grandparents could have told you how many electric motors they owned. There was one in the car, one in the fridge, one in the vacuum cleaner, and they probably owned a dozen in total. Today we have no idea and it’s not a meaningful question, but we probably do know how many devices we own with a network connection. Again, our children and grandchildren will have no idea, and it won’t matter. 

In both of these cases, a wave of commodity components enabled a wave of product creation. The electrification of the home was enabled by cheap DC motors, heating elements and so on, and the current wave of ‘smart home’ devices is enabled by cheap and low power cameras, wifi chips, microphones and so on (mostly coming out of the smartphone supply chain).  

Equally, in both of these cases there’s a discovery phase: we may have all of these components but we still have to work out the right ways to combine then. Hence, people proposed all sorts of electric devices for the home, and we collectively worked out which made sense and where - everyone in Britain has a kettle, most people in America have a blender, and no-one has an electric can opener. 

The same is happening with ‘smart home’ now. Lots of ideas for products are being tried - some will be the kettles and some will be the can openers, and it will only be  obvious which in hindsight. Part of this process is also working out where the company value goes - which things are commodities from the existing manufacturers (oven companies, locks companies etc), which are commodities from Shenzhen, and which are opportunities for new company creation.  .... " 

Machine learning has a lot of the same questions: how do we combine these commodity components into products that make sense - both in the home and on platforms and smartphones? 

Part of the challenge of machine learning is not just working out what problems to solve but working out how to surface that to the user. Some of this may just be branding - we may need to say “this is ‘AI’” to set expectations (and also to lower them).  .... "