There’s a specific type of person I’ve noticed applying to jobs, participating in ML communities, or writing to me online: software engineers with an interest in machine learning. Their ML background typically consists of a course or two from Andrew Ng [https://www.coursera.org/courses?query=machine%

Ask them if AI will kill all humans. Actually, anything along these lines will work. When will we achieve 100% automation? When are we going to build a machine that is better than humans at every kind of work? These are questions I often get at talks, interviews, or one-on-one

It’s often assumed you need a number of PhDs and double the number of developers to create useful machine learning (ML) solutions. This is only sometimes true. If you’re creating leading-edge products — meaning you’re developing brand new machine learning methods — then you will certainly need a team

I’ve often needed to enter a domain where I previously had no expertise: e.g. when I started my blog, when I decided to consciously work on my social skills, or when I decided I want to understand business better. Getting an initial understanding of the new domain is

I’m reading a book on happiness and meditation which contains the following story. In Chinese history, during the reign of Emperor Shun (who lived sometime around 2200 BCE), what was then known as China was plagued by frequent destructive floods along the Yellow River. The emperor ordered a nobleman