Humans possess a powerful ability to reason. They understand a question asked by a fellow human-being and provide the most appropriate answer to it. A human brain can do quick mathematics to answer a trivial question like "If I have 10 balls and bought two cans, each having 5 balls, how many balls would I have?" The humans can do commonsense reasoning like "If a driver sees a pedestrian on the crossover, what would he do?" Humans have intelligence in understanding if somebody is cutting a joke and probably get a deeper understanding of what the speaker really wants to say? The question is, can we train the machines to gain this kind of intelligence that we humans possess?

Anyone who has dabbled in multiple domains notices how principles and meta-narratives in one area carry over to others with surprising frequency. For example, Satya Nadella (Microsoft's CEO) often compared strategies from the sport of cricket to business strategies in his autoethnography about turning Microsoft around [1]. Steve Covey does something similar in Seven Habits of Highly Effective People with occasional reflections to his Mormon faith. In Fooled By Randomness, Nassim Taleb draws parallels between principles of randomness he observed in financial markets to other aspects of life, including business. This disquisition is of that genre. I've been an autodidact most of my life. But after I started working in the field of machine learning, I came to understand some amusing but useful parallels between human learning and machine learning. Now granted, despite all the hype about machine learning (better known by the moniker "artificial intelligence" in popular media), machines don't learn like humans do.