This book has the right blend of mathematical detail and practical applications to get anyone excited about statistical thinking. I discovered Nate Silver early in my high school years and quickly took a liking to his work.  For me, he turned a stereotypically dry subject into the most fascinating area of study. The array of fields this book touches (economics, baseball, poker, weather forecasting, and more) showcases the widespread value of statistical thinking. I particularly loved the contrast between the recent improvements in weather forecasting with the continued confoundment with earthquake prediction.  Weather forecasts have become considerably more reliable than those of 20 or 30 years ago, primarily due to the positive correlation between their accuracy and the computing power available. Earthquake prediction, on the other hand, has not seen this correlation. Its signal-to-noise ration remains quite low. I believe this is the single best book out there to introduce a reader to Bayesian inference and its numerous real-world applications. I've recommended The Signal and The Noise to multiple friends and family members as a must read.

In my semi-ordered rankings, I would designate The Signal and The Noise and Algorithms to Live By as '1a' and '1b,' respectively. I enjoy this book's application of Computer Science theory to everyday problems. The section on Optimal Stopping Theory really shaped my view of life as an optimization problem with time being the primary constraint. (See my YouTube video on this theory and The Rationalization of Love for more.) The introduction to sorting theory, caching, and Big-O notation was helpful for someone coming from a non-CS background. The chapters on Bayes' Rule and scheduling were the most familiar at my time of reading, since I had worked through this content at length in my undergraduate curriculum in Industrial Engineering. I've recommended this book to a number of people with backgrounds in STEM fields.

The subject of the most inspiring book on this list, Steve Jobs was the visionary who stood at the intersection of the arts and sciences. His obsessive nature and unrivaled stubbornness defined his professional and personal journey. Two key themes were Jobs' attention to detail and desire to tightly control the user experience. Although my general philosophy is more practical in nature, this book made me appreciate the significance of addressing the seemingly minute details in product design and presentation. Jobs' desire for control explains his vehement opposition to the uncoupling of software and hardware, a stance that put him opposite Bill Gates and the majority of the computer world. While I credit Steve Jobs as an exceptional artist and businessman, his technical knowledge does not come close to those of his Apple co-founder Steve Wozniak, Gates, or fellow Isaacson biography subject, Elon Musk. 

In terms of personality intrigue, I think Jobs actually tops Elon Musk and others making this list. The absurd stories detailing a fruit-only diet and copious LSD use during his hippie college years were one of the few times I have laughed out loud while reading a book. Furthermore, his "reality distortion field" ensured he would always Think different. But maybe all the absurdity necessary for his success. After all, "the people who are crazy enough to think they can change the world are the ones that do."

I had to update this list after reading another Elon Musk biography in 2023. Both the Vance and Isaacson biographies held my interest at the respective time of my reading, but since the Vance book came first, I will give it the "credit" on this list. (Walter Isaacson isn't left out to dry either, as a number of his books appear on this list.) It wouldn't shock me to see another high-profile Musk book released in the coming years. His enigmatic personality and boundless undertakings consistently render him a prime candidate for biographic study.

Elon Musk's life story offers unparalleled intrigue. I believe he makes a strong case as the most influential man in the world during the 2010s and 2020s. (He was recognized as Time Person of the Year in 2021.) His personal sacrifice in launching SpaceX and driving Tesla Motors forward serves as inspiration for this young engineer. The stories revealed both a quirky personality and a man relentlessly pursuant of monumental ambitions. I believe there are lessons, both positive and negative, to draw from Elon Musk as I embark on my career journey. My favorite bit from the Vance biography was Musk's late night email rant regarding unnecessary acronym usage by his SpaceX employees. Elon Musk is undoubtedly a unique mind, but it was his ability to persevere through physical and emotional hardship that stood out most. My view is that while his methods are often unorthodox and demanding, there is little doubt that his ambitions are rooted in a humanitarian worldview.

The events involving Elon Musk from 2015-2023 naturally make Isaacson's biography significantly longer than Vance's. There were stories from each of PayPal, Tesla, and SpaceX that appeared in both books, but the combination of Isaacson's writing talent and the developments during this 8-year period between respective publishing dates made reading the newer biography worthwhile. Elon Musk has undoubtedly become a more controversial figure in recent years. I think his chaotic Twitter takeover and increasing forays into political discourse are ultimately reducing the probability of achieving his ultimate goal of making humans a multi-planetary species. Still, his incredible track record of success at the intersection of science and business leads me to estimate his probability of achieving these lofty goals higher than for anyone else on the planet.

Despite the story being exaggerated from its real-life basis, the world of the MIT card counting team was captivating. I enjoy the writing style of Mezrich and a story about a group roughly my age. My game of choice at the casino will always be Texas Hold'em Poker and never Blackjack; this is because I recognize the edge the house holds over me in the latter. Statistically, one should never play Blackjack, Craps, Roulette, etc. because you will not win in the long run (the Law of Large Numbers is undefeated). This calculus changes, however, when you have a team of MIT students counting cards and varying bets to give themselves a slight edge over the house. Multiply the small edge by very large bets and you end up with large winnings (and some angry pit bosses).

This is an essential read for anyone in the manufacturing or Industrial Engineering space, in my opinion. The Theory of Constraints can guide efforts to improve manufacturing efficiency at any level. I was first assigned to read this as part of my freshman Introduction to Industrial Engineering course at USC. I referenced this multiple times in the years following, as I made my way into manufacturing engineering internships. To my delight, this book was referenced during a talk by our site IE/Manufacturing branch manager at Texas Instruments while I was interning at the company in 2023. The story is an excellent jumping off point for understanding the challenges of lean manufacturing. Remember the lessons of Herbie the Bottlenecker!

The common themes of my favorite books are clearly present at this point in the list. The real-world instances of Expected Value, The Law of Large Numbers, Base Rate Fallacy, and more showcase the value in statistical/mathematical proficiency. I've always believed this skill is harder to acquire and refine than an intuitive understanding of physical phenomena; there often isn't a physical component to reference and performing trial and error testing is more difficult with delayed feedback. My only major critique is that Ellenberg's tendency to venture down alleys of (excessive) nuance make this less readable than the top 2 books on my list. His background in academic mathematics is very apparent in his discussion of proofs and the historical contributions of various mathematicians. Some standout moments were the missing bullet holes problem, gaming the Massachusetts lottery, and Pascal's wager. Overall, while slightly heavy in "academic-speak," it is a highly enjoyable read for mathematically inclined individuals like me.

The Physics of Everyday Things may not top my list overall, but it has the most practically useful knowledge of all the books here. At a very high level, all of engineering is converting between electrical, mechanical, and thermal (heat) forms of energy. The devices that comprise our modern standard of living are each genius innovations in converting between energy forms to carry out a function. The book is set up as a walk through a typical day in life, breaking down your interactions with each device to the physical fundamentals. These explanations showcase a 'first-principles' approach to understanding and problem solving (similar to the methods of the another subject on this list, Elon Musk.) The classical mechanics of pendulums and springs help explain clocks and AC power generation. The properties of electromagnetic forces help explain CPUs, analog-digital (and vice-versa) signal conversion, MRIs, and so much more. The explanation of field effect transistors has to be my favorite section, though, because of my work experience. This book provides an excellent foundation for a basic understanding of physical phenomena while maintaining readability and relative conciseness.

In contrast to the "lone genius" theme of Isaacson's Steve Jobs and Elon Musk biographies, his narrative of the innovation of the personal computer and the internet centers around organizational collaboration. In a world of endless intellectual property battles, it's important to remember that every "invention" builds off the work of predecessors. The spotlight on the early contributions of Ada Loveless, Jon von Neumann, and Alan Turing to the world of computing introduced me to thinkers who were all well ahead of their respective times. Turing's predictions on the future of computing and machine intelligence now seem particularly prescient. Jumping forward to the 1960s, the stories of the invention of the semiconductor and integrated circuit were of personal interest to me. (Texas Instruments' own Jack Kilby gets special attention!) Moving from hardware to software, the founding of Microsoft by Bill Gates and Paul Allen redefined the personal computer market and sparked the "open vs. closed" discussion at the heart of modern software debate. It's another fantastically crafted Isaacson story and serves as a nice complement to his work on Steve Jobs.

Tetlock's research deserved praise for shattering any justifications the intelligence community had for gatekeeping forecasts regarding world affairs. But the forecasting shortcomings of "experts" isn't solely limited to the intelligence community. The research covered a wide range of topics including economics and domestic politics, in addition to foreign affairs. From its beginnings under IARPA, the Good Judgment Project tournament brought forward a group of "super forecasters' who regularly outperformed the "experts" in matters of prediction. Finding is "super forecaster" appears to be rare. The total population of "super forecasters" is likely less than 1% of the population. Interestingly, they come from a variety of cultural and professional backgrounds. What sets them apart? The discussion around the traits that make a forecaster "super" is similar in theme to Nate Silver's The Signal and The Noise. One takeaway was that being well-read in a number of areas is key (time to get that NYT subscription renewed). In addition to this well-informed empirical basis, one much be willing to regularly adjust estimates. In summary, you need to be a really good Bayesian thinker.

Biotechnology, and genetic engineering specifically, is my bet for the industry that will have the greatest impact on humanity over the next 50 years. CRISPR-Cas9 appears to be the "molecular scissors" that will enable widespread genetic modification in humans. The overwhelming majority of academic work never reaches the public view, but Jennifer Doudna's pioneering research in ribosomal RNA and CRISPR delivery mechanisms gets its spotlight from my favorite author, Walter Isaacson. The difficult balance between upholding academia norms of collaboration and frantically racing with competing labs to publish papers and patent technologies was a theme throughout the book. Feng Zhang's team at the Broad Institute served as the primary competition for Doudna's team on CRISPR-Cas9 research. This competition made it apparent that academics are not immune to the selfish motivations of profit and, more significantly, recognition. Lastly, I think Isaacson did a good job raising pertinent ethical questions regarding the future of human genetic modification. To be open about my priors, I am largely an unabashed supporter of liberal human genetic modification. I see the potential benefits of eliminating human disease as far outweighing the risks. I must concede, however, that some caution around germline editing will be needed in the coming years. The accomplishments of Doudna and others keep me optimistic regarding the scientific community's ingenuity and humanity's desire to use this technology productively.

This book should serve as a source of hope for those who are willing to dismiss improvement in mathematical acumen as an impossibility. I agree with the premise that scientific and mathematical thinking is largely pattern recognition. I try to live my life around the idea of continuous improvement, so this message of training your brain to do anything certainly resonated with me. It should be acknowledged, though, that I grew up in a family of STEM backgrounds and have always carried a strong aptitude for these fields. To better gauge this book's value, I try to recommend it to the more mathematically-averse people in my life.

I'm always excited to read stories from my favorite sport, baseball. Moneyball (book and film) fused my distinct nerd and jock loves of statistics and America's Pastime. Despite being a diehard Dodgers fan, I was also able to appreciate Ben Reiter's Astroball and the way Jeff Lunhow was able to set up a dynasty in Houston. (It should be noted that I read this book before the cheating revelations of the 2019 offseason.) The analytics revolution in the baseball world over the past two decades has been incredible and much of it can be traced back to Billy Beane. We all know that a true baseball fan of the 2020s cares not about batting average but about expected weighted on-base average (xwOBA)!

Is aging avoidable? Since I had no prior exposure to Dr. Sinclair's research, I came into this book with the largest possible range of expectations on his anti-aging conclusions. Anything along the spectrum from total quackery to medical genius was a possibility. (Are medical opinions Normally distributed along such a spectrum? Among the general population, anecdotal evidence suggests a heavy skew in favor of 'quackery.') I came out of this book highly intrigued, yet unconvinced regarding the grandest claims the author put forward.

I strongly agree with Dr. Sinclair's central view that aging should be viewed as a disease that we must eradicate rather than accepting as a 'natural' part of life. He also makes a great distinction on the difference between a "healthspan" and a lifespan. Things get interesting, however, when it comes to the scientific detail informing his hypothesis. he presents a viewpoint that mammalian aging is a function of epigenetic factors, rather than genetic ones. It has to be noted that his seemingly promising results in rodent studies and subsequent extrapolations have generated significant pushback within the scientific and medical communities. My other critique is that this wasn't the smoothest of reads due to all the technical jargon. Despite the questionable science and the low readability, I wanted to include this work because it spurs intriguing conversations on human longevity.