The author starts off his book using the example of flash crash and an e-bay bidding algo wreaking havoc. He cites these examples as an indication of the extent to which multiple algos dedicated to ONE single task, i.e.bots, are being used in various domains. Obviously the start of algos and heightened excitement for it came from Wall Street. But the author tries to give a journalistic account of all the various places where bots are being used. This book is a light read. It gives examples of interesting people who are using bots to do things that were unthinkable a few years ago, thanks to the super cheap computing power and the ignition( word borrowed from Talent code) given by popular wall street quants, Page&Brin’s and Zuckerbergs of the world.

In this post, I will briefly mention the people mentioned in this book as well as the bots that they have created.

Wall Street, the First Domino


Thomas Peterfyy

I found the first chapter of the book to be the most interesting story in the entire book. It tells the story of Thomas Peterfyy’s, a Hungarian immigrant, who lacking a full engineering degree, founded one of the most successful companies in the algo trading space, Interactive Brokers. The story is written in Michael Lewis style. where the writing is fast paced and appears like fiction, the only difference being its not. Peterfyy innovations made him a billionaire after hacking for 20 years on Wall Street.

A brief history of man and algorithms

In a space of 20 pages, this book gives a superfast recap of the developments that lead to information age. The rockstars of the story are Fibonacci, Leibniz, Gauss, Bernoulli, Pascal, Euler, George Boole, Babbage, Lovelace, and Claude Shannon.

The Bot top 40( Bots in the music industry)

I found this chapter to be second best in the entire book. It talks about four stories of how bots are making waves in the music industry.

  • Mike McCready and his Music X ray venture that is revolutionizing the way songs are chosen by various music bands and record companies.

  • Success story of Pandora.

  • David Cope creates three revolutionary bots – Emmy that recreates Bach’s music, Howell that gives successful opera concerts and Annie that composes new songs based on machine learning

  • Professor Jason Brown , a math PhD uses algos to solve some of the highly debated questions about Beatles songs and chords used in some of their hits.

The Secret Highways of Bots

This section talks about Daniel Spivey and  his venture “Spread Networks”, a firm that specializes in providing fiber-optic communication infra between NY and Chicago to Algo traders. All said and done, financial industry has been a big reason for innovation in the tech industry. Determining the next field to be invaded by bots is the sum of two simple functions: the potential to disrupt plus the reward for disruption.

For a long time, that equation yielded the largest total on Wall Street, which is why so many of our smartest people, from engineers to physicists to PhDs, began flocking there. Still, that collection of brainpower didn’t stop the industry from seeding economic disaster in 2008.That Wall Street would bring the world to the edge of anarchy and then go whistling into the night is hardly surprising. That’s a condition that may never change. But what does change, almost daily, is the hardware and technology available to grappling traders and their algorithms.

The story of how Wall Street’s technology has evolved is important because its progress eventually flowed to the rest of the economy. Even in the case of Spread Networks, a fiber-optic tunnel built for Wall Street, its effects have already leaked beyond the small world of algorithmic traders. Spivey and Barksdale’s line now carries broadband to small towns that didn’t have it. Spread is transferring large medical image files for hospitals and doctor’s offices. The company offers these non– Wall Street entities lit fiber at affordable prices— an opportunity that exists only because algorithmic traders were willing to shell out millions for exclusive strands of Spread’s dark fiber.

Gaming the System (Bots in Sports and Entertainment)

  • Deep Blue (1997) – A bot that could analyze 200 million chess positions / second as compared to Kasparov’s 3 /second. 

  • Watson (2011) – IBM’s bot for Jeopardy game

  • Tuomas Sandholm – CMU professor’s effort to create an algorithm to play poker, using game theory. Still a long way to go to incorporate the irrational behavior and other complex human variables. Building a world-class poker bot is so hard as algorithms aren’t very good at predicting, analyzing or gaming irrational human behavior

  • Andrew Gilpin applied poker algos to stock market and has managed a hedge fund since 2010

  • Cantor Fitzgerald’s Midas algo that allows betting on sporting games

  • Bruce Bueno de Mesquita- Political science professor who uses game theory algorithms. He predicted the fall of Hosni Mubarak amidst a small group of investment managers at a Wallstreet firm. He was later asked to sign a non disclosure agreement. The Wallstreet firm then took a massive position to capture this prediction and made a ton of money.

  • Billy Beane and his stats algos for baseball– Moneyball fame

  • Prof Galen Buckwalter – The man who created the algos behind eHarmony, a dating site. The site says it now has a hand in more than 2 percent of marriages in US. , i.e. 120 marriages per day

  • Four math grads from Harvard use algos for their venture OkCupid, another popular dating site.


Paging Dr.Bot ( Bots in the medical field)


  • Al Roth uses game theory algorithms to match kidney donors and patients.

  • Dr. Brent James at Intermountain Medical Center in Utah uses data and algorithms to improve hospital performance . Managed to cut the death rate of coronary bypass surgery to 1.5% compared with 3% nationally.

  • AirStrip – Algos that provide real-time patient data straight to doctor’s iPhones, iPads

  • Nick Patterson, a Wall Street hacker , after eight years at Renaissance now writes algos to find , search and sort patterns and relationships from the DNA data. He is changing the speed at which DNA can be analyzed

  • IBM’s bot for healthcare , a modified version of Jeopardy bot, was given a job at Well point , a giant health insurer to assist doctors in their offices with diagnoses, providing a valuable and legitimate second opinion

Categorizing Humankind ( Bots in the Personality Analysis)

  • NASA’s  head psychiatrist involved in developing people-assessing algorithms to select teams for various missions

  • Taibi Kahler , a psychologist at Purdue uses algos to categorize people. These algos are used in NASA, prepping up Presidential speeches and host of other places.

  • Kelly Conway uses algos at eLoyalty, a consultancy for companies with large call centers

  • Peter Brown and Robert Mercer language and speech recognition algos are used in a lot of softwares now. In fact they were so successful that they joined Renaissance and now co-head Renaissance after Jim Simon’s retirement

Wall Street Versus Silicon Valley + Wall Street’s loss is a gain for the rest of us

These sections talk about the boom and bust of algo trading talent war. In years preceding to the financial crash, most of the talented Math and Physics Ivy league grads headed to Wall street. There was a massive need for such grads to write algos , apply math to complex derivate pricing and valuation, hft algos etc. The result of this lead to talent scarcity in many fields that were crying for algos. Soon things started to change. There are many factors that lead to grads turning down Wall Street offers. Firstly, the crisis, Secondly, the Zuckerberg-Twitter-Groupon-Dropbox-Zynga effect, i.e. technology firms were using a ton of AI, algos, bots to create apps on the internet. There is a mention of Jeffrey Hammerbacher who worked as a quant at Bear Stearns, left it to join facebook and created a ton of algos that help facebook in making the site sticky. He now heads Cloudera, another startup that uses quant stuff to manage data storage. The author cites of examples where grads have turned down offers from even Renaissance and says that they are indications that things are changing and people no longer want to end up applying math and algos for Wall Street.

The Future belongs to Algorithms and their creators

The last section of the book gives a few cues that give a sense of the ways bots are going to change and influence things in the future. What about the talent ? Are there are enough math grads and programming majors who can program these bots in various fields that are crying for algo solutions ? This question in the book leads to a discussion on the state of US education sector and the faculty at the junior school level. One of the solutions pointed out by many experts, deans, professors, tech visionaries is to expose kids at the junior school level to math and programming. Programming should be made compulsory to everyone at a high school level. The book ends with the following suggestion:

There are a lot of potentially quantitatively minded people roaming around out there who have never given their brains a proper crack at the game. Smart people aren’t in short supply. Smart people educated in quantitative fields are, however. We just need to increase the size of the funnel that gets people there. Every single student at every high school in America should be required to take at least one programming class. Most students will stop there and move on to do something else. But even if just 5 percent of those students become engaged with the power of devising their own programs and algorithms, it will change the dynamic of our education system and our economy. Imagine all of the students who never give programming or quantitative fields a thought. Math, to them, is a rote skill that must be memorized so that a test or a quiz can be passed; they never see the other side of math that’s changing our world. Or when they finally do, perhaps in college, their life vector is already set toward another field. Programming and computer science classes shouldn’t be relegated to a niche group of students— this is the skill, more than any other, that will matter during this century. All students should get their chance.