Hi! My name is Krishna Rupanagunta. I write about the art and science of decision making: from the huge opportunity that AI presents in the Enterprise world (my day job) to the endlessly fascinating complexities of the human brain and what that means to how we as individuals and societies make choices, big and small.

I deeply enjoy reading on a smorgasbord of topics: Economics, History (American and Indian), Technology and of late, Psychology. Fiction makes its way every once in a while. I will share my reading list and whenever I can, write up my review of the book as well. And if you are up for a book discussion, you can always reach out to me.

I would love to hear from you – feel free to leave a review/comments on my posts, and if you do want to go beyond that, my email: rsrikrishna1@gmail.com.

The Cognitive Enterprise

Data and AI is transforming the Enterprise like never before. And I am fortunate to be in the thick of how this is playing out in companies, big and small.

Random Musings

My thoughts on a wide variety of topics, that try and explore the human mind: how we think and how we make decisions

Book List

I read – and by conventional measures, read a lot. The list of books that I am reading/have read with my own little review

Learning from other disciplines (..continued)

Last week, we looked at how quantum physics can teach us a thing or two about problem solving in small data environments. Some of the most path breaking work in Physics started with a theory, refined by mathematical models and then proved (or disproved) with experiments. This week, let’s take a look at Biology –… Continue Reading →

Problem Solving: Learning from other disciplines

Richard Feynman (he doesn’t need an introduction) was a consummate problem solver. When asked about his problem-solving techniques, his colleague Murray Gell-Mann (a Nobel Laureate himself) defined the ‘Feynman Problem Solving Algorithm’: Write down the problem Think very hard Write down the answer While this was partly in jest, this to me captures why it… Continue Reading →

Solving hard problems

Over the last few posts, I had explored the overall idea of how to approach the problem of decision making in a world of ‘tail events’ and insufficient data. And increasingly, it is clear that most Analytics teams in organizations are not very well equipped to navigate this order of complexity. Over the next couple… Continue Reading →

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