Safari an O’Reilly Media Company. - AI for People and Business

After earning my masters degree in applied mathematics (awarded with distinction), I became an IndyCar race car engineer and race strategist who competed in more than 100 races worldwide, including many times in the Indianapolis 500. I also ran the vehicle dynamics and data science department at Andretti Autosport, which helped drive results for a four-car IndyCar racing team.

In American professional motorsports, winning the Indianapolis 500 is the ultimate goal. I attended my first Indianapolis 500 when I was still in high school. If youve never been, I highly recommend it. This event is truly the greatest spectacle in racing and is the largest single-day sporting event in the entire world. The track itself is the largest sporting facility in the world in terms of capacity.

The first year I attended, 1992, turned out to be the closest Indy 500 finish in history (and still is), and ended with Al Unser, Jr., beating Scott Goodyear for the win by 0.043 seconds! Think about that! Thats less than half of one tenth of one second after racing for almost three hours, at an average speed of 220-plus mph, and for 500 miles (the equivalent of driving from Chicago to Toronto)!

I was so blown away that I walked out of the Indianapolis Motor Speedway (IMS) that day telling those with me that I would someday work in IndyCar racing, and the rest is history. Additionally, and very serendipitously, my racing career began with me working for Al Unser, Jr., the driver who won that very same Indy 500 that I attended as a kid. I came on board as chief assistant engineer to Alan Mertens, the engineer who designed the car with which Unser won in 1992!

shows an image of an article in Racer magazine following the 2007 Indianapolis 500, where I was the race engineer and strategist for Davey Hamilton. Im shown on the right celebrating a ninth place finish after starting 20th, this was Daveys remarkable comeback race following 23 surgeries to reconstruct his legs and feet after a horrific and massive crash at the Texas Motor Speedway in 2001.

Figure P-1. Racer Magazine 2007 Indianapolis 500 article (reprinted from RACER Magazine with permission)

As my racing career progressed, I quickly learned that professional motorsports involves generating competitive advantage on steroids. Racing at that level requires intense innovation, continuous optimization, perfection, advanced analytics of inordinate amounts of data, rock-solid teamwork and collaboration, and the ability to execute and adapt on the fly at an often unrealistic pace. All of this while under intense pressure and accountability. Ultimately, professional motorsports is all about maximizing insights to driveand benefit fromdecisions, actions, and outcomes in the least amount of time possible. This is how competitive advantage and top results are produced.

As an IndyCar race car engineer and race strategist using AI, machine learning, and data science to optimize race car setups and race strategy for a given combination of driver, track layout (super speedway, short oval, road course, street course), and conditions (weather, track surface), I was able to help my teams win many races and podium finishes, including winning the historic final Champ Car (formerly CART) race in Long Beach, California. I worked directly with many notable drivers and team owners, including Michael Andretti, Al Unser, Jr., Jimmy Vassar, Will Power, Tony Kanaan, Danica Patrick, and Ryan-Hunter Reay to name a few.

You might be wondering what this has to do with this book, the framework its about, and AI in general? The answer is everything! Let me explain.

After about 10 years in racing, I decided to transition into the tech industry. I quickly realized that, much like in racing, companies are also constantly trying to beat their competitors to win. One thing that quickly became clear to me is that what it takes to win races doesnt apply only to racing, but also to companies, regardless of industry or size. Although the definition of winning might be different for every company (e.g., achieving specific business profit and growth goals), what it takes to win is the same. In both racing and business, winning, and especially winning consistently, requires competitive advantage, which is the ability to understand, act, and achieve performance levels in ways that your competitors cant.