Thoroughly enjoyed this no BS talk by Manoj Bhargava. [youtube https://www.youtube.com/watch?v=x46-XiMOoJE?rel=0]

The paper titled, “Statistical Modeling – The two cultures”, by Leo Breiman(man behind CART) was published 14 years ago, a time when machine learning techniques had started to become popular. In the last decade or so, the field has exploded. There are many graduate and PhD programs that are offering full-fledged courses on the subject. There are also dedicated journals that publish ML research findings of researchers from a wide range of fields.

If one rips apart a computer and looks at its innards, one sees a coalescence of beautiful ideas. The modern computer is built based on electronics but the ideas behind its design has nothing to do with electronics. A basic design can be built from valves/water pipes etc. The principles are the essence of what makes computers compute. This book introduces some of the main ideas of computer science such as Boolean logic, finite-state machines, programming languages, compilers and interpreters, Turing universality, information theory, algorithms and algorithmic complexity, heuristics, uncomutable functions, parallel computing, quantum computing, neural networks, machine learning, and self-organizing systems.

The author tries to answer two questions via this book : What are the core elements of a fulfilling work ? How should we make a change to our current path so that our work is in line with our being. Give meaning to work The author talks about five aspects relevant to work : earning money achieving status making a difference

In this post, I will attempt to briefly summarize the main points of the book An optimistic skeptic The chapter starts off by saying that there are indeed people in the world who become extremely popular, make tons of money, get all the press coverage, by providing a perfect explanation, after the fact. The author gives one such example of a public figure who rose to fame explaining events post-fact, Tom Friedman.