Here are 100 books that Computers Ltd. fans have personally recommended if you like
Computers Ltd..
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I grew up in farm country of central Indiana. But spent my summers on an island in northern Ontario with my grandparents. My grandfather was a self-taught naturalist and shared his love and fascination of the world around us with me. I went on to become a geologist and traveled the globe exploring for natural resources. My love of nature and science is the foundation for the science fiction I write. Whether a proven theory, a fantastical hypothesis, or true science fiction, it’s all based on science fact. It allows everyone to learn about a world built in science fiction which one day may exist in science fact.
This is a book that is at once a biography, a testament to human genius in the face of imminent danger, and a story of human injustice. Alan Turing had an idea about a ‘universal machine’. A machine, when built at Bletchley Park, allowed the Allies in World War II to crack the German Enigma ciphers. This universal machine laid the foundations for modern computing and all the amazing advances we enjoy today. But at a price for Turing, he fought inner demons about his homosexuality and eventually paid the ultimate price.
I marveled at his genius, cheered his cryptographic successes with each cipher cracked, shouted against the tragedy of his arrest, cried at his untimely death. A death at his own hand at the age of 41. The world lost a genius due to a society’s labelling of homosexuality as a crime.
A NEW YORK TIMES BESTSELLER The official book behind the Academy Award-winning film The Imitation Game, starring Benedict Cumberbatch and Keira Knightley It is only a slight exaggeration to say that the British mathematician Alan Turing (1912-1954) saved the Allies from the Nazis, invented the computer and artificial intelligence, and anticipated gay liberation by decades--all before his suicide at age forty-one. This New York Times-bestselling biography of the founder of computer science, with a new preface by the author that addresses Turing's royal pardon in 2013, is the definitive account of an extraordinary mind and life. Capturing both the inner…
I boast a two-decade-long career in the software industry. Over the years, I have diligently honed my programming skills across a multitude of languages, including JavaScript, C++, Java, Ruby, and Clojure. Throughout my career, I have taken on various management roles, from Team Leader to VP of Engineering. No matter the role, the thing I have enjoyed the most is to make complex topics easy to understand.
This book profoundly influenced my thinking process, combining the worlds of mathematics, art, and music. I was captivated by how the book explores the deep connections between Gödel’s incompleteness theorems, Escher’s art, and Bach’s art of counterpoint.
The book’s puzzles and thought experiments pushed me to think more abstractly and critically. Despite being dense, I found it incredibly rewarding and eye-opening. I recommend this book to anyone interested in logic, creativity, and the nature of human thought. It’s a masterpiece!
Douglas Hofstadter's book is concerned directly with the nature of maps" or links between formal systems. However, according to Hofstadter, the formal system that underlies all mental activity transcends the system that supports it. If life can grow out of the formal chemical substrate of the cell, if consciousness can emerge out of a formal system of firing neurons, then so too will computers attain human intelligence. Goedel, Escher, Bach is a wonderful exploration of fascinating ideas at the heart of cognitive science: meaning, reduction, recursion, and much more.
I’m a professor of computer science at Oregon State University. My research focus is on programming languages, but I also work on computer science education and outreach. I grew up in Germany and moved to the United States in 2000. Since computer science is a fairly new and not widely understood discipline, I am interested in explaining its core ideas to the general public. I believe that in order to attract a more diverse set of people to the field we should emphasize that coding is only a small part of computer science.
This book is not about computing, but it is relevant in an indirect way. I love this book, since it is written in such an engaging style and illustrates with many examples that math is not a dry subject to be practiced only by mathematicians but helps everyone to solve real-world problems. The book shows how important it is to be precise in describing problems and that applying a little mathematical rigor goes a long way in solving them. Ellenberg describes mathematics as the “extension of common sense by other means.” In a similar way, I view computer science as the extension of problem-solving methods (aka “algorithms”) by other means.
"Witty, compelling, and just plain fun to read . . ." -Evelyn Lamb, Scientific American
The Freakonomics of math-a math-world superstar unveils the hidden beauty and logic of the world and puts its power in our hands
The math we learn in school can seem like a dull set of rules, laid down by the ancients and not to be questioned. In How Not to Be Wrong, Jordan Ellenberg shows us how terribly limiting this view is: Math isn't confined to abstract incidents that never occur in real life, but rather touches everything we do-the whole world is shot through…
I am an academic researcher and an avid non-fiction reader. There are many popular books on science or music, but it’s much harder to find texts that manage to occupy the space between popular and professional writing. I’ve always been looking for this kind of book, whether on physics, music, AI, or math – even when I knew that as a non-pro, I wouldn’t be able to understand everything. In my new book I’ve been trying to accomplish something similar: A book that can intrigue readers who are not professional economic theorists, that they will find interesting even if they can’t follow everything.
In the ongoing debates over artificial general intelligence (AGI), Judea Pearl is taking a firm stand: He argues that an intelligent robot should be able to reason about causality and that the currently fashionable approaches to AI miss this aspect.
A celebrated AI researcher and a Turing Prize laureate, Pearl has developed an amazingly original approach to this problem. This book is a high-end popular exposition of his approach.
But it’s so much more than that. It’s a history of statistics and its conflicted attitude to causality. It’s a story of heroes (or villains?) in this history. And it’s a scientific autobiography that describes Pearl’s journey. Pearl likes picking fights with the AI community, statisticians, or economists. He’s boastful, provocative, extremely intelligent, and knows how to tell a story.
'Wonderful ... illuminating and fun to read' - Daniel Kahneman, winner of the Nobel Prize and author of Thinking, Fast and Slow
'"Pearl's accomplishments over the last 30 years have provided the theoretical basis for progress in artificial intelligence and have redefined the term "thinking machine"' - Vint Cerf, Chief Internet Evangelist, Google, Inc.
The influential book in how causality revolutionized science and the world, by the pioneer of artificial intelligence
'Correlation does not imply causation.' This mantra was invoked by scientists for decades in order to avoid taking positions as to whether one thing caused another, such as smoking…
Saying just the right words in just the right way can cause a box of electronics to behave however you want it to behave… that’s an idea that has captivated me ever since I first played around with a computer at Radio Shack back in 1979. I’m always on the lookout for compelling ways to convey the topic to people who are open-minded, but maybe turned off by things that are overly technical. I teach computer science and study artificial intelligence as a way of expanding what we can get computers to do on our behalf.
I always find myself applying algorithmic thinking in my everyday life—it affects the way I put away dishes, navigate to the store, and organize my to-do lists. And I think others could benefit from that mindset.
So, when I read this book, my reaction was "Yes! That's what I want people to know. I just wish I could have said it that well!" The authors (who I know, but didn't know they wrote a book together), did a fantastic job of selecting algorithms with deep human connections. Really! And they explain them just right, without getting too mathematical but while still hitting the key ideas with clarity and accuracy. Fantastic!
A fascinating exploration of how computer algorithms can be applied to our everyday lives.
In this dazzlingly interdisciplinary work, acclaimed author Brian Christian and cognitive scientist Tom Griffiths show us how the simple, precise algorithms used by computers can also untangle very human questions. Modern life is constrained by limited space and time, limits that give rise to a particular set of problems. What should we do, or leave undone, in a day or a lifetime? How much messiness should we accept? The authors explain how to have better hunches and when to leave things to chance, how to deal…
It was while on the job as an investment banker that I first heard about this new thing called Bitcoin, before the word "web3" entered the vernacular. Initially I was skeptical but curious. But I became convinced the underlying technology of blockchains was ushering in nothing short of a new internet. My father Don Tapscott and I agreed to collaborate on a major research initiative that became the international best-seller, Blockchain Revolution. Since then, I have traveled to 40 countries and seen first-hand how blockchain and now Web3 is changing the world, setting the stage for a new digital age. My new book charts a course for this coming transformation.
In The Innovators, Walter Isaacson reminds us that “innovation occurs when ripe seeds fall on fertile ground.” Like the earth beneath our feet, we stand on stratum upon stratum of technological innovation, each with unique markers of its age.
Sometimes, the right idea, person, or group of people arrives at the right time to sow the seeds of something new. Isaacson explores how this phenomenon, teaching us how the collaboration of many individuals working across time and space helped usher in the first digital age in a highly readable survey of the main players and events.
As we stand on the brink of a second digital age, we would do well to search our history for lessons before stepping into the future.
Following his blockbuster biography of Steve Jobs, The Innovatorsis Walter Isaacson's story of the people who created the computer and the Internet. It is destined to be the standard history of the digital revolution and a guide to how innovation really works.
What talents allowed certain inventors and entrepreneurs to turn their disruptive ideas into realities? What led to their creative leaps? Why did some succeed and others fail?
In his exciting saga, Isaacson begins with Ada Lovelace, Lord Byron's daughter, who pioneered computer programming in the 1840s. He then explores the fascinating personalities that created our current digital revolution,…
The author was the chief Silicon Valley writer for The Wall Street Journal during the first of the 1990s. He went on to become an acclaimed scholar in the history of science, engineering, and innovation. At the peak of his journalism career, the Boston Globe described Zachary as the most talented reporter on the Journal's staff. Zachary went on to write technology and innovation columns for The New York Times, Technology Review, and Spectrum magazine. Zachary has also taught courses on science and technology studies at Stanford University, UC Berkeley, and Arizona State University, where he was a professor from 2010-2020. He lives in northern California.
The software interface for Apple’s innovative Macintosh was largely (and legally) modeled on system software designed at the Palo Alto < California research center of Xerox, an East Coast photocopy company whose stodgy executives failed to realize the value of the coding breakthroughs they had funded and nurtured in the heart of northern California’s computer cauldron. Before anyone at the top of Xerox realized the enormity of their errors, the company had licensed to Steve Jobs and Apple key software technologies that animated the Macintosh revolution in the 1980s. Hiltzik’s richly detailed and readable history, based on scores of interviews, is the best account of the epic failure of an American corporate icon. Apple and Jobs went on to achieve glory while Xerox ultimately became a zombie company, having missed the greatest industrial wave of the past 75 years.
During the 1970s and 1980s, a number of brilliant computer eccentrics were thrown together by Xerox at the Xerox PARC centre in Palo Alto, California. These people created inventions such as the first personal computer, the graphic user interface, the mouse and one of the precursors of the Internet. However, the bosses at Xerox never really appreciated these men or their innovations, and accused them of just fooling around. Then along came the outsiders, such as Steve Jobs of Apple Computing, who left the PARC with ideas that they would later exploit and make vast fortunes on, propelling them to…
I’m a professor of computer science at Oregon State University. My research focus is on programming languages, but I also work on computer science education and outreach. I grew up in Germany and moved to the United States in 2000. Since computer science is a fairly new and not widely understood discipline, I am interested in explaining its core ideas to the general public. I believe that in order to attract a more diverse set of people to the field we should emphasize that coding is only a small part of computer science.
This book is about the design of artifacts that are used by humans. It discusses, in particular, how specific features of cognitive artifacts can support or impede their effective use. The physical artifacts discussed in this book provide concrete illustrations for some abstract computer science notions such as types. I have used some of the examples successfully in talks about computer science for the general audience. A focus of this book is on representations, which plays an important role in many areas of computer science. If you enjoy the examples discussed in this book and like to think about representations, then you are thinking like a computer scientist.
In Things That Make Us Smart, Donald A. Norman explores the complex interaction between human thought and the technology it creates, arguing for the development of machines that fit our minds, rather than minds that must conform to the machine.Humans have always worked with objects to extend our cognitive powers, from counting on our fingers to designing massive supercomputers. But advanced technology does more than merely assist with thought and memory,the machines we create begin to shape how we think and, at times, even what we value. Norman, in exploring this complex relationship between humans and machines, gives us the…
I have been coding for over 30 years. I’ve seen some miserable interfaces, and some large programs that collapse under their own weight. Software was, at one point, notorious for being late, over budget, and unreliable. These books have helped turn the corner on these failings, and I have found each of them very valuable in my day-to-day programming. While you can learn technique and even languages online, the kind of insight found in these books is rare and worth spending time and money on.
This book changed my entire perspective on writing the UI and UX of great software. Even the revised edition is a bit old but still has many valuable lessons to teach. Platt established many of the fundamental principles of writing usable and transparent software, and his book should be read not only by designers, but perhaps especially by programmers.
This non-technical book discusses the annoyances and dangers we encounter every day when using computers. Written with delightful wit and humor, as well as the insight of an experienced insider, it rips into the design of software much as Atul Gawande's Complications exposed the practice of medicine. Its basic message to ordinary people having problems learning or using their software is this: It's not your fault! It's not because you're dumb! Aimed primarily at casual users of software, the book tells readers what they should expect from their software and how to make their voices heard so that they receive…
It’s been fantastic to work in computer vision, especially when it is used to build biometric systems. I and my 80 odd PhD students have pioneered systems that recognise people by the way they walk, by their ears, and many other new things too. To build the systems, we needed computer vision techniques and architectures, both of which work with complex real-world imagery. That’s what computer vision gives you: a capability to ‘see’ using a computer. I think we can still go a lot further: to give blind people sight, to enable better invasive surgery, to autonomise more of our industrial society, and to give us capabilities we never knew we’d have.
Richard’s authoritative leading textbook excellently describes the whole field of computer vision. It starts with the sensor, moves to image formation followed by feature extraction and grouping, and then by vision analysis. It’s pragmatic too, with excellent descriptions of applications. And there is a ton of support material. This is a mega textbook describing the whole field of computer vision.
Computer Vision: Algorithms and Applications explores the variety of techniques commonly used to analyze and interpret images. It also describes challenging real-world applications where vision is being successfully used, both for specialized applications such as medical imaging, and for fun, consumer-level tasks such as image editing and stitching, which students can apply to their own personal photos and videos.
More than just a source of "recipes," this exceptionally authoritative and comprehensive textbook/reference also takes a scientific approach to basic vision problems, formulating physical models of the imaging process before inverting them to produce descriptions of a scene. These problems are…
