Sadly I missed Aspen Words Presents Michael Lewis & Malcolm Gladwell in conversation back in May. Admittedly, it is fun to see both Michael Lewis and Malcolm Gladwell together again talking about the backstories of their books.
I have recently finished both books, Michael’s The Premonition and Malcolm excellent story from WorldWar II, The Bomber Mafia.
Thanks to Apsen Words for sharing this event. Enjoy the conversation.
Grokking Algorithms: An Illustrated Guide For Programmers and Other Curious People by Aditya Y. Bhargava. Aditya is an Engineering Manager at Etsy. He blogs at adit.io.
This is not a book for seasoned programmers. However, this is certainly a wonderful book to learn the basics of algorithms.
Grokking Algorithms provides an illustrated overview of algorithms which certainly provides a foundation to common algorithms used everyday by programmers.
For anyone interested in learning the basic structures of algorithms, Aditya also provides code samples in Python. In addition, the programming community has shared java versions of the book on Github.
On the surface, everyone learning about various algorithm options will not secure a programming job in their short term future.
However, I feel it is very fair to say many readers interested in learning about algorithms will not be overwhelmed.
If you are interested in learning to code, then this book is required reading. There are 400 illustrations within Aditya’s 256 page book. easy-peasy. The 256 page count is not lost on me.
Algorithms of Oppression: How Search Engines Reinforce Racism
by Safiya Umoja Noble. Safiya is an associate professor at UCLA and is the Co-Founder and Co-Director of the UCLA Center for Critical Internet Inquiry. Safiya’s research as a result, considers how bias has been embedded into search engines.
Clearly, search engine algorithms are not neutral by any means. This was indeed proving to be a very disturbing issue at the time of publication in 2018.
So, how did this happen in the first place? It is rather shocking to understand that a seemingly simple search term “black girls” results in such disgusting results.
Safiya certainly reveals this unforgiving gap and Google has made efforts to fix their errors. The result of her work has brought about the term algorithmic oppression.
Safiya explores how racism, especially anti-blackness, is generated and maintained across the internet, yet is focused squarely on Google.
In addition, Safiya reveals the impact of AdWords, Google’s advertising tool. I found it interesting that since search results are altered by paid advertising, Google is more of an advertising company than a search engine company.
The Master Algorithm: How the Quest for the Ultimate Learning Machine Will Remake Our World by Pedro Domingos. Pedro is Professor Emeritus of Computer Science and Engineering at the University of Washington.
In 2018 he launched a machine learning research group at D.E. Shaw, but departed after one year. Shaw’s well known former employees include Jeff Bezos, Lawrence Summers and Cathy O’Neil, author of Weapons of Math Destruction.
The Master Algorithm is a wonderful inspection of Machine Learning technology. However, do not be intimidated, this book is not for computer science majors. Pedro is addressing Machine Learning for consumers. The benefit here is the concepts around Machine Learning for every day consumers.
Actually, the goal of the book is two fold: learn about the development of machine learning, and then inspire the reader to build a master algorithm of their own. Do not worry, there is no coding in this book.
So, the premise for Pedro is to strive to build a master algorithm, which in turn will generate all algorithms needed by human kind. While a bit ambitious, it does not feel an out of bounds question. As Pedro conveys, give it twenty years. This is powering Google, Amazon, Microsoft in the enterprise and Apple’s iPhones.
Machine Learning is surpassing the parent, Artificial Intelligence as the most popular deployment of advanced computing over the last twenty years. What is remarkable is that only within the last ten years the integration of advanced processors and cloud computing, with quantum elements are now making the long promise of Machine Learning possible.
Algorithms to Live By: The Computer Science of Human Decisions by Brian Christian and Tom Griffiths. Brian is the author of The Most Human Human, a Wall Street Journal bestseller, New York Times editors’ choice, and New Yorker favorite book of the year. Tom is a professor of psychology and cognitive science at Princeton University. In addition, he directs the Institute of Cognitive and Brain Sciences.
At first glance the idea of brining algorithms into our daily lives seems a bit too much, even for a budding computer nerd. At the same time, Brian and Tom prove that most of us are already doing this daily.
I recall spending many hours programming SQL while living in Chicago and realizing how much more efficient my grocery shopping would be if I actually transformed my shopping list into a SQL table:
SELECT * FROM FoodGroup
ORDER BY GroceryStoreIsle;
So I can certainly agree. Yet this idea still may seem daunting. If you begin thinking about repeating tasks you perform, even laundry should certainly make you believe there is a better way.
Algorithms will certainly make this possible. Therefore, you may be spending too much time repeating tasks. This is where the book reveals how you can become efficient, by sharing the history and development of many common algorithms. You will certainly discover a few frameworks.