Winchester has written a captivating history of engineering. He starts in England, during the Industrial Revolution, and shows how standards of measurement developed at that time have since spread across the world. Winchester shows how precision is paramount to the correct functioning of most devices in use today - from everyday tools like cameras and cars, to the most sophisticated machines, like satellites and the LHC.
The most advanced reference for Deep Learning. Aggarwal starts with the basics, showing how classical Machine Learning methods (Regression, SVMs, etc) are special cases of Neural Networks. He then quickly jumps into the most sophisticated topics: CNNs, RNNs, Neural Turing Machines, GANs, etc. The book is very well researched, provides plenty of exercises and is superbly organized. A must!
Hayashi presents the mathematics behind one of the most promising fields of research today, starting with the basics (Hilbert Spaces, Tensor Products, etc). Many advanced topics are presented in detail, such as Quantum Teleportation, the Reverse Shannon Theorem, Superdense Coding, Quantum Error Correction (QEC) and Quantum Cryptography. The exercises are well chosen, their solutions are provided and the book is very well organized.
Kai-Fu Lee reviews the ongoing US-China rivalry in the field of AI, showing what challenges lay ahead for Silicon Valley companies (especially Google). Lee believes that the US-China rivalry is not a zero-sum game and that both sides stand to gain enormously by cooperating on certain issues, like AI regulation. He shows how AI is expected to render unemployed tens of millions of people worldwide and discusses whether UBI is an appropriate solution to this problem.
This is the second edition of Vance's famous biography of Elon Musk - updated with new material up to January 2017. It is my favorite biography ever, for many reasons: Vance's writing style, Musk's personality, the epic history of SpaceX & Tesla, etc. The driving theme of the book is Musk's endless resilience - his ability to deal with extraordinary challenges while having few resources. Vance also goes into Musk's future plans, especially about the Gigafactories.
Mark Manson wrote a sometimes dark, sometimes hilarious, but deeply honest book on living a carefree life. He wants us to understand that not being extraordinary is ok and that we benefit greatly from knowing our limitations. Since we are limited in both time and ability, being able to distinguish what matters from what doesn't is crucial. The book also has many limitations, but it makes for good airplane reading.
Tom Holland narrates the rise and fall of the Roman Republic and the beginning of the Empire. He starts with the legendary founding of Rome then quickly shifts to the late Republic. Holland follows all the major characters of the period - Pompey, Crassus, Caesar, Mark Anthony, Cicero and Augustus - showing how each dealt with new realities created by the others. The book ends with a discussion on how Augustus was able to restore stability after half a century of civil wars and coups.
Galloway presents what made Amazon, Google, Apple and Facebook so successful - what these four have that other companies in Silicon Valley don't. He shows how those companies have managed to tap into basic human needs (thinking, consuming, caring, etc) as a means of selling their products. Galloway also believes that Amazon is now pulling away from the other three, threatening them directly in areas they are dominating (ex: Amazon vs Google in online search).
Recommended by Musk, Hinton and LeCun, this is the best introduction to Deep Learning there is. It assumes only a minimal mathematical background and spends a lot of time introducing the necessary concepts from Linear Algebra, Probability, Numerical Computing and classical Machine Learning. The fundamentals of Neural Networks are then presented: ANNs, CNNs, RNNs, GANs, etc. Some advanced topics like Deep Belief Networks are also briefly discussed.
Martin has written a great introduction to writing clean code and refactoring. I read this book for the first time when I was still at McGill and have reread it since, as it provides all kinds of useful advice: how to avoid side-effects in functions, how to write good comments for said functions, good rules to follow when programming in teams, etc. It should be mandatory reading for junior programmers.
Together with Norman Davies' Europe, Merriman's book is a reference in the field of European History. Merriman shows how, over the last five centuries, power and wealth gradually shifted from Southern Europe (the Ottoman Empire, the Italian Republics, Habsburg Spain and Austria) to Northern Europe (France, the Netherlands, England and Germany). Major topics like Protestantism, Imperialism, Nationalism and the Industrial Revolution are all covered in great detail.
This is possibly the most terrifying book ever written about AI. Barrat goes into all the great risks posed by this new technology: from abuse by governments and corporations, to machines ultimately taking over. He explains that a fully conscious AI will want to survive, just like we do, and that we may quickly find ourselves competing against a being far more intelligent than us. The book was recommended by Elon Musk on Twitter and it's easy to see how it shaped his views.