The Vancouver archipelago. Lots of land high enough to adapt to climate change, rich fisheries, access to fresh water, diverse community with less racism than most places.
There is an assumption that anything worthwhile is available on the web. About half of what I read is only available in print (mostly older books of poetry, math and music). I spend enough time looking at and working on screens that when i read I prefer physical books with all of their delightfully different form factors.
Yes, constantly, and as wide a mix as interest and attention affords. I also try to read books from many different cultures and across a wide time span. Just reading books from the past five years impoverishes thinking, especially in fields like AI that have deep roots and where a current standard approach is stifling the imagination (as much as I likes using Keras and Tensorflow).
Judea Pearl Causal Diagrams and analysis techniques. This will become central to a lot of AI and data analysis over the next decade. I also brushed up on Monte Carlo modelling, being able to understand and think in terms of uncertainty and risk and to have a probabilistic turn of thought is also important going forward.
My wife and I have chosen to live in Vancouver twice. Once in 1989 after ten years in Tokyo (8) and Copenhagen (2) and again in 2012 after six years in Cambridge MA. I grew up in Montreal. We chose Vancouver for some simple reasons. Direct flights to Tokyo, decent sushi, a culturally diverse environment in which to raise our multicultural children (now grandchildren), an interesting arts scene (in the 80s and 90s, it has declined as housing prices have gone up) and a relatively open society and political system. Economic opportunity was not a factor as I have always worked globally. I also prefer to be off centre, a bit away from the cities that think they are important like the Bay Area, NYC, Tokyo, Toronto, London etc. as I find that little of deep creative interest comes from these places. Innovation thrives on the edges and where different cultures rub up against each other.
I find this silly to the point of absurdity. I spend far too much time online, read laterally as much as vertically, and have no trouble reading books. I spend 1-2 hours a day reading books of all sorts and have never noticed this attention gathering issue. My kids, who grew up online, also read books and do not seem to have this issue. My granddaughter, who interacts with the Internet mostly through voice at this point (yes, my son has one of those devices and it is interesting to ask her what she thinks she is talking to when she has a conversation with Google) is also quite able to sit down and read a book and spends about an hour reading to herself most days. I don't think any of us are special. I think this is an invented claim being used to make a polemical point.
Not sure that I think in my sleep, but I definitely think on long bike rides, has to be more than 60 km though. I will sometimes set up a problem and then let it churn as I turn the crank. Restful and stress reducing too.
My learning style is Abstract, Connected, Historical, Written, Social
This means I need to understand the theory first and work down to practical examples (many people learn the other way around but not me). I need to understand how one set of abstractions or theories connects to others that I may understand better. I like to go back to origins, understand motivations, follow the evolution, and see what paths are thought to be dead ends (like machine learning was thought to be a dead end by many people around 2005). I only really understand things if I write them down and preferably write about them. I learn best when I learn with other people, my wife jokes that when I want to learn something I start a company.
Given my learning style, yes, I need to be learning several things in parallel, helps with the connections. I also tend to read too quickly so having three or so learning themes at any time helps me to slow down and reflect.
I have been tracking my learning in granular detail for about ten years using Excel. I am also tracking it on TeamFit.co Every year I build a learning plan (goals, resources, evidence) and track against that.
I am really looking forward to reading this. Please start a discussion thread on this on the LinkedIn Design Thinking group as well. Really important work.
What you are talking about is a penetration pricing strategy. These generally fail. They are a good idea if (i) there are real first mover advantages or (ii) there is a steep learning curve or (iii) there are strong internal network effects. Preferably you have two of these. This is not true of most enterprise solutions. Generally, companies that adopt penetration pricing strategies do not generate enough cashflow for sustained innovation and are displaced by the services that invest in such innovation. Or, the service becomes completely commoditized and is often taken over by some form of open source option.
Fascinating question. Every year I develop a learning plan covering major themes (some of these have been going on for more than a decade), specifics inside the theme, how I think I will learn, whose help I will need (person or community), how I will pay back this help or pay it forward, what evidence I will have of the learning ... I also try to make sure that there are at least a few things each year that cross two or three themes. I have a long-term theme on pricing and this year I am spending a lot of time studying platform business models, so I have a set of specific actions that combine the two: organize a one-day event on platform business models, lead the pricing session at this event; advise at least one client on a platform pricing model (I still do some consulting as it help me to learn and share what I am learning); write some blog posts on pricing in platform business models; stretch goal - build some tools to help design platform pricing models and share them.