Book Club: The Art of Doing Science and Engineering
Why I loved this book & little tips to learn and think well :)
Knowledge doubles every 17 years, and 90% of the scientists who ever lived are now alive.
-R. Hamming
Intro
Welcome to my first book review! I am excited to start this “book club series” and it gets me to read more. And we start with a really brilliant book.
"The Art of Doing Science and Engineering: Learning to Learn" by Richard W. Hamming is my Roman Empire. I work at a startup operating in the AI field, which grows in the fast-changing market of AI agents, large language models, and technology advancements. A fundamental part of my job is to stay on top of the evolving knowledge.
This means that often, someone asks: Who should I follow to keep up with all the news in tech? What smart people should I follow on X or LinkedIn? What newsletters should I subscribe to? What should I read to understand X, Y, or Z?
I invariably find myself unable to provide good answers. I think this book makes me realize, among other things, why these aren’t the most optimal questions to ask, for they misunderstand the nature of learning in an era of exponential information growth.
I think Hamming’s book is actually a career book, a self-help book, a diary, and a textbook all at once. And that’s what I love about it. Let’s go.
Why is the author legit?
Richard Hamming (1915-1998) was a pioneering mathematician and computer scientist who fundamentally shaped computing and information theory. He is generally regarded as the founder of coding theory, creating concepts like Hamming codes, Hamming distance, and Hamming window.
During his career, Hamming really did a lot. He worked at:
Los Alamos National Laboratory on the Manhattan Project (1945-1946)
Bell Telephone Laboratories (Bell Labs) for 30 years (1946-1976), where he did his most influential work
Naval Postgraduate School as a professor (1976-1998).
Fun Fact: A popular but unverified story claims that when working on the Manhattan Project at Los Alamos, Richard Hamming was once asked to review calculations about “the probability that the test bomb will ignite the whole atmosphere.”
What’s the book about
In “The Art of Doing Science and Engineering”, Hamming shares insights acquired during his career and examines the systems that enable rapid and high-quality learning.
Paradoxically, the book isn't primarily about technical content—though it covers the digital revolution, computing history, coding theory, information theory, digital filters, simulation, and more. Rather, it focuses on "style of thinking" and approaches to solving problems creatively. It feels like looking right into Hamming’s mind or just talking to him. That being said, don't get overwhelmed by the technical parts; they are integral to the experience. Grasping the mathematical concepts may require additional time, depending on your background knowledge. However, a lot of the insights are understandable without the technical details.
The book's subtitle is "Learning to learn". There are some explicit points about learning (which I am sharing below), but the biggest takeaways are implicit. The learning reader is supposed to learn is demonstrated by how Hamming thinks about and challenges the topics in the book, how he sense-checks the established facts, how he estimates and calculates, and how he finds parallels to different concepts. Of course, I also learned new knowledge, e.g., how early the first computers were constructed, but the big learning is how to think about things better.
This book is concerned more with the future and less with the past of science and engineering. Of course future predictions are uncertain and usually based on the past; but the past is also much more uncertain—or even falsely reported—than is usually recognized. Thus we are forced to imagine what the future will probably be.
-R. Hamming
Hamming's primary aim is to prepare students for careers in rapidly evolving technical fields by teaching them adaptability and self-directed learning. The book's central themes—learning how to learn, developing personal thinking systems, and self-education in emerging fields—make this essentially a career development guide disguised as a technical text. It offers reassurance about navigating uncertain career paths through chapters on experts and systems engineering.
The book culminates with "You and Your Research," where Hamming advocates for pursuing excellence rather than mere survival, highlighting courage, drive, and comfort with ambiguity as essential traits for significant achievement in science and engineering.
Learning to learn (and think)
Here are just a few of the great and practical ideas for developing a good thinking and learning system. I am taking some from Hamming’s book, but not all of them are explicitly mentioned there; some of them just occurred in my mind or are based on experience.
Look at fundamentals
Try to recognize patterns
Question assumptions by regularly asking "Why do we do it this way?"
Get mere exposure to knowledge
Compare to whatever is comparable
Take ideas to their logical extremes to test their limits
Have a notebook with good thoughts and ideas
Visualize abstract concepts
Study thinkers from other disciplines to broaden your approach
Practice quick "envelope calculations" to build intuition before doing detailed work. I would say envelope calculations are just "vibe calculating", making approximations, but using good logic and rules of inference
Try to be a leader (in thought), not a follower
Challenge experts, question established thinking
Focus on fundamentals rather than details since details become obsolete while fundamentals endure
Have a person or community to discuss your ideas with
Try explaining the concepts to someone (or to an imaginary audience)
Try to simplify the concept in your mind
Test what you learned on something you already know.
I read the book with Wikipedia articles in the other tabs and a notebook for my thoughts open on my coffee table.
Every section could be enough for one individual book; it's ambitious in the topics it chose (e.g., how is mathematics defined, physics, history, …) but I assume the point was really what the title of the book says. However, it's a pity that Hamming didn't write even more.
What I liked
I like Hamming's "meta-thinking," a mixture of experience (and hence intuition, creating patterns, seeing the bigger picture) and pure intelligence. His ability to abstract is one of the greatest things about this book.
What really makes this book special is how it seamlessly blends "hard" technical knowledge (like information theory) with what I would call storytelling. I love that it teaches theory in a fun way, it's like Richard talking to me and discussing with me. I feel like I can see his thinking on paper really 1:1. I love how Hamming comments on the processes and discoveries of other scientists. It feels very "behind the scenes" even though they are decades or centuries apart.
I love seeing him quote so much ("knew”, "seem", “understand”) because he doesn't want to overexplain how he means or he emphasizes the meaning is relative.
It is important to notice, while I have indicated maybe we can never understand Quantum Mechanics in the classical sense of “understand”, we have never-the-less created a formal Mathematical structure which we can use very effectively. Thus, as we go into the future and perhaps meet many more things we cannot “understand”, still we may be able to create formal Mathematical structures which will enable us to cope with the fields.
I have put the word "understand" in quotes because I do not even pretend to know what I mean by it.
-R. Hamming
I think Richard Hammings does “vibe writing”. And, as I mentioned, I appreciate how much life and career advice there is.
In forming your plan for your future you need to distinguish three different questions: What is possible? What is likely to happen? What is desirable to have happen?
-R. Hamming
Some other cool quotes from the book:
With almost 70 years, and no decent explanation of the (wave-particle) duality, one has to ask, “Is it possible this is one of those things we cannot think?” Or possibly it is only it cannot be put into words. There are smells you can not smell, wave lengths of light you cannot see, sounds you cannot hear, all based on the limits of your sense organs, so why do you object to the observation given the wiring of the brain you have then there can be thoughts you cannot think?
Von Neumann in his classic work on Quantum Mechanics proved there were no hidden variables, meaning there was no lower structure and Nature was essentially probabilistic—a point Einstein never would accept. But the proof was found to be fallacious, new proofs found, and in their turn found to be fallacious—the current situation being a toss up as to what you want to believe.
Man is not a rational animal, he is a rationalizing animal. Hence you will find that often what you believe is what you want to believe rather than being the result of careful thinking.
The first rule of systems engineering is: If you optimize the components you will probably ruin the system performance.
What I didn’t like that much
I would say the style of writing is less structured than you would expect. It’s not a carefully planned textbook, but rather, it's a sequence of thoughts on certain topics (e.g., computers or data). In my opinion, it sometimes makes the book lack a coherent flow between topics, making it feel more like a collection of excellent lectures than a unified narrative.
I found the book to be a bit misleading in terms of its degree of rigor. It mixes frequent envelope calculations or diagrams but does not properly establish a common language that would really add value in some cases (e.g., "system"—or, to be more precise, "formal system" in the part about math or "design" in the information theory part). If we want to be technical, it would make it easier for the reader to process the thoughts and be sure about the common ground faster.
Even though there is no formal prerequisite to the book, the thinking systems themselves need to be developed through practice. The patterns and intuition in the technical parts come naturally to me after years of training, so I am not sure how long the book would take me to process without a mathematical background.
Education is what, when, and why to do things, Training is how to do it. Either one without the other is not of much use.
-R. Hamming
Indeed, it's supposed to be advanced. As Hamming mentions, he assumes the reader to know things.
I’ve seen missed opportunities to explain some concepts really well. For example, "axiom" wasn't explicitly mentioned but was walked around so closely in the math chapter. I think math is very often misunderstood, not only from the philosophical view (e.g., what school you prefer for your POV of what math is) but also from the practical view - how theories are constructed and how axioms are chosen.
What’s next in the bookclub
The next more complex book I'm reading is Material World. However, I left it on my bedside table on a different continent, so feel free to recommend me other interesting books in the meantime.
