I’ve tweeted some notes about my favorite blog post from 2006, Kathy Sierra’s Crash course in learning theory.
I just finished Ian Bremmer’s latest book Us vs. Them: The Failure of Globalism. To me, the most interesting part of the book was chapter 3, where Ian, an acclaimed political scientist, talked about the outlook of the 12 most-important developing economies (according to Ian):
- 🇿🇦 South Africa
- 🇳🇬 Nigeria
- 🇪🇬 Egypt
- 🇸🇦 Saudi Arabia
- 🇧🇷 Brazil
- 🇲🇽 Mexico
- 🇻🇪 Venezuela
- 🇹🇷 Turkey
- 🇷🇺 Russia
- 🇮🇩 Indonesia
- 🇮🇳 India
- 🇨🇳 China
In particular, I found Ian’s analysis of the two Sub-Saharan African countries (🇿🇦 South Africa and 🇳🇬 Nigeria) most interesting.
Don't try to be an influencer. Try to be a nerd instead. Don't maximize your impact. Maximize your interest instead.
In my 20s, I tried to become an influential person - and that was one of the biggest mistakes I made.
Here’s some (very) quick takeaways from fast.ai’s Computational Linear Algebra course, lecture 4.
Here’s some (very) quick takeaways from fast.ai’s Computational Linear Algebra course, lecture 3.
Yesterday I wrote some of my favorite quotes from “Factfulness” by Hans Rosling. There was one quote I left out, the one about “bad and better.”
The best quotes from “Factfulness” by Hans Rostling, the book Bill Gates called “one of the best books I’ve read in a long time”
I just read Factfulness: Ten Reasons We’re Wrong About the World—and Why Things Are Better Than You Think by the late Hans Rosling, his son Ola Rosling, and his daughter-in-law Anna Rosling Rönnlund.
Bill Gates called it “one of the best books I’ve read in a long time”. Read his full review here.
Here are some of the quotes I liked (emphasis mine).
As someone who studied interface design in college and has worked as a designer/frontend engineer, I loved “Using Artificial Intelligence to Augment Human Intelligence” by Shan Carter and Michael Nielsen. Here are the three quotes I especially liked (emphasis mine).
Here’s some (very) quick takeaways from fast.ai’s Computational Linear Algebra course, lecture 2.