Here are 100 books that A Brief History of Artificial Intelligence fans have personally recommended if you like
A Brief History of Artificial Intelligence.
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My passion for generative AI first ignited in 2016 when I spoke about it at a conference, and ever since then, I can’t stop! I've created an online course, a newsletter and even wrote a book to spread knowledge on this groundbreaking technology. As an instructor, I empower others to explore the boundless potential of generative AI applications. Day in day out, I assist clients in crafting their own generative AI solutions, tailoring them to their unique needs.
I truly believe that this is the book that brought my generation of AI experts into the fold. Despite having studied AI and ML, this book took me by the hand and grounded me in the fundamentals. I love the fact that it covers everything from mathematical basics to industry-level techniques.
Written by the OGs of deep learning, it's an absolute must-read for anyone serious about the field. Highly recommend for students and engineers alike.
An introduction to a broad range of topics in deep learning, covering mathematical and conceptual background, deep learning techniques used in industry, and research perspectives.
“Written by three experts in the field, Deep Learning is the only comprehensive book on the subject.” —Elon Musk, cochair of OpenAI; cofounder and CEO of Tesla and SpaceX
Deep learning is a form of machine learning that enables computers to learn from experience and understand the world in terms of a hierarchy of concepts. Because the computer gathers knowledge from experience, there is no need for a human computer operator to formally specify all…
It is April 1st, 2038. Day 60 of China's blockade of the rebel island of Taiwan.
The US government has agreed to provide Taiwan with a weapons system so advanced that it can disrupt the balance of power in the region. But what pilot would be crazy enough to run…
As a child of the microcomputer revolution in the late 1970s, I’ve always been fascinated by the concept of a general-purpose machine that I could control. The deep learning revolution of 2010 or so, followed most recently by the advent of large language models like ChatGPT, has completely altered the landscape. It is now difficult to interpret the behavior of these systems in a way that doesn’t argue for intelligence of some kind. I’m passionate about AI because, decades after the initial heady claims made in the 1950s, AI has reached a point where the lofty promise is genuinely beginning to be kept. And we’re just getting started.
Goodfellow’s Deep Learning is a must in the field because it was the first. Prince’s new book is an essential follow-up to be up-to-date with the latest model types, including diffusion models (think Stable Diffusion or DALL-E), transformers (the heart of large language models), graph networks (reasoning over relationships), and reinforcement learning.
The math level is similar to what you’ll find in Goodfellow’s book.
An authoritative, accessible, and up-to-date treatment of deep learning that strikes a pragmatic middle ground between theory and practice.
Deep learning is a fast-moving field with sweeping relevance in today’s increasingly digital world. Understanding Deep Learning provides an authoritative, accessible, and up-to-date treatment of the subject, covering all the key topics along with recent advances and cutting-edge concepts. Many deep learning texts are crowded with technical details that obscure fundamentals, but Simon Prince ruthlessly curates only the most important ideas to provide a high density of critical information in an intuitive and digestible form. From machine learning basics to advanced…
As a child of the microcomputer revolution in the late 1970s, I’ve always been fascinated by the concept of a general-purpose machine that I could control. The deep learning revolution of 2010 or so, followed most recently by the advent of large language models like ChatGPT, has completely altered the landscape. It is now difficult to interpret the behavior of these systems in a way that doesn’t argue for intelligence of some kind. I’m passionate about AI because, decades after the initial heady claims made in the 1950s, AI has reached a point where the lofty promise is genuinely beginning to be kept. And we’re just getting started.
Artificial intelligence is, of necessity, an academic pursuit, at least initially. McCorduck’s book is her account of the history and development of AI. She was not a historian coming to events after the fact but a living witness. Her circle of friends included all the key figures, the people those of us who fell into AI later didn’t have the opportunity to know.
This book, personal and human, not technical and heavy, reveals the humanness of the process. Yes, artificial intelligence was the goal, but human intelligence (and frailty) were central to its emergence.
In the autumn of 1960, twenty-year-old humanities student Pamela McCorduck encountered both the fringe science of early artificial intelligence, and C. P. Snow's Two Cultures lecture on the chasm between the sciences and the humanities. Each encounter shaped her life. Decades later her lifelong intuition was realized: AI and the humanities are profoundly connected. During that time, she wrote the first modern history of artificial intelligence, Machines Who Think, and spent much time pulling on the sleeves of public intellectuals, trying in futility to suggest that artificial intelligence could be important. Memoir, social history, group biography of the founding fathers…
A Duke with rigid opinions, a Lady whose beliefs conflict with his, a long disputed parcel of land, a conniving neighbour, a desperate collaboration, a failure of trust, a love found despite it all.
Alexander Cavendish, Duke of Ravensworth, returned from war to find that his father and brother had…
As a child of the microcomputer revolution in the late 1970s, I’ve always been fascinated by the concept of a general-purpose machine that I could control. The deep learning revolution of 2010 or so, followed most recently by the advent of large language models like ChatGPT, has completely altered the landscape. It is now difficult to interpret the behavior of these systems in a way that doesn’t argue for intelligence of some kind. I’m passionate about AI because, decades after the initial heady claims made in the 1950s, AI has reached a point where the lofty promise is genuinely beginning to be kept. And we’re just getting started.
Alan Turing’s 1936 paper “On Computable Numbers, with an Application to the Entscheidungsproblem” was foundational to the development of computer science. To this day, Turing machines, the theoretical computational devices imagined in Turing’s paper, are a research cornerstone as they embody the concept of “computable.” If a programming language can implement a Turing machine, then the language is deemed Turing complete and is, therefore, general-purpose enough to implement any algorithm.
Turing’s paper is readable, but Petzold’s book breaks it down in minute detail to explain the nomenclature and meaning behind Turing’s words. I believe all computer science students should study this paper, and you’ll be hard-pressed to find a more thorough review than the one presented in this book.
Programming Legend Charles Petzold unlocks the secrets of the extraordinary and prescient 1936 paper by Alan M. Turing
Mathematician Alan Turing invented an imaginary computer known as the Turing Machine; in an age before computers, he explored the concept of what it meant to be computable, creating the field of computability theory in the process, a foundation of present-day computer programming.
The book expands Turing's original 36-page paper with additional background chapters and extensive annotations; the author elaborates on and clarifies many of Turing's statements, making the original difficult-to-read document accessible to present day programmers, computer science majors, math geeks,…
I spent over forty years developing complex, software-intensive systems, and the Association of Computing Machinery honored me with the title of distinguished engineer. AI and robotics have been my main technical focus for the last 5 years. For the last couple of years, I have been binge-watching videos on advances in AI and robotics and binge-reading books on the topic. I am also a multi-award-winning author of science fiction novels and short stories. Most of the short stories in my coming book involve AI and robots.
I really loved this book because of its wide breadth. If you are only going to read a single book on AI and its ramifications, this would be my top recommendation.
It covers everything from the history of artificial intelligence to what the short- and mid-term future will look like. This book provides a solid foundation to help you prepare for a future dominated by AIs and robots.
"Machines of Tomorrow offers a fascinating journey into the future of AI, providing a unique perspective that combines technology, economics, geopolitics, and history." — PASCAL BORNET, Technology Influencer, 2 million followers.
How AI Will Shape Our World.
Written in an easy-to-read style accessible to everyone, "Machines of Tomorrow" grounds the reader in a thorough history and description of Artificial Intelligence, enabling an appreciation of its real trajectory and ultimately a deeper level of engagement with the core concept of the book: what should societies expect from AI in the coming decades?
I was stimulated by Norbert Wiener’s “Cybernetics” to study circuits in the brain that control behavior. For my graduate studies, I chose the olfactory bulb for its experimental advantages, which led to constructing the first computer models of brain neurons and microcircuits. Then I got interested in how the smell patterns are activated when we eat food, which led to a new field called Neurogastronomy, which is the neuroscience of the circuits that create the perception of food flavor. Finally, because all animals use their brains to find and eat food, the olfactory system has provided new insights into the evolution of the mammalian brain and the basic organization of the cerebral cortex.
The other books in this series are mostly about the real brain. But artificial intelligence promises us a new enhanced brain. What does the future hold? Terrence Sejnowski is a neuroscientist who was one of the first to realize the potential of AI. Since he has been there from the start, in this book he gives the reader an exciting inside story on the people and the advances that are reshaping our lives.
Early attempts at AI were limited, but once computational power took off big computers running multilayer neural nets began proving that they could defeat humans at the most demanding games, enhance human capabilities such as pattern recognition, text recognition, language translation, and driverless vehicles, and work to obtain rewards, just like a human. While these advances are dramatic, it is well to remember that the networks are built not from representations of real neurons, but rather from…
How deep learning—from Google Translate to driverless cars to personal cognitive assistants—is changing our lives and transforming every sector of the economy.
The deep learning revolution has brought us driverless cars, the greatly improved Google Translate, fluent conversations with Siri and Alexa, and enormous profits from automated trading on the New York Stock Exchange. Deep learning networks can play poker better than professional poker players and defeat a world champion at Go. In this book, Terry Sejnowski explains how deep learning went from being an arcane academic field to a disruptive technology in the information economy.
The Duke's Christmas Redemption
by
Arietta Richmond,
A Duke who has rejected love, a Lady who dreams of a love match, an arranged marriage, a house full of secrets, a most unneighborly neighbor, a plot to destroy reputations, an unexpected love that redeems it all.
Lady Charlotte Wyndham, given in an arranged marriage to a man she…
I fell in love with technology when I wrote my first computer program at age 14 when there was no public Internet, no personal computers, no iPhone, no cloud. I have made technical contributions to every era of computing from mainframes, to PCs, Internet, Cloud, and now AI. I was recently elected to the National Academy of Engineering. AI currently surpasses my wildest imagination on the art of what’s possible. I'm still passionately working in technology at Google focused on how to live healthier lives. I believe we can make AI the telescope of the future, to helping everyone live long and healthy lives.
This book explores how AI is transforming healthcare and the potential benefits it can bring to patients and doctors.
The author, Eric, is a cardiologist with working knowledge of technology of AI. I love how he describes with clarity, the present and potential to make people healthier with AI First thinking. That is, how AI can make the business of health care human.
I love the premise and basis of Eric’ thinking that we can make healthcare personalized, proactive, anticipatory, helping people live healthier lives and reducing the cost of healthcare.
At the same time he is mindful that AI could be used to dehumanize healthcare and exacerbate existing inequalities.
A visit to a physician these days is cold: physicians spend most of their time typing at computers, making minimal eye contact. Appointments generally last only a few minutes, with scarce time for the doctor to connect to a patient's story, or explain how and why different procedures and treatments might be undertaken. As a result, errors abound: indeed, misdiagnosis is the fourth-leading cause of death in the United States, trailing only heart disease, cancer, and stroke. This is because, despite having access to more resources than ever, doctors are vulnerable not just to the economic demand to see more…
I have been writing for many years, and my main preference is political thrillers with criminal overtones. I first became interested in politics when I worked at several political conferences in the 60’s and 70’s. I have been involved in several criminal cases, including my own, and within my family, I have a nephew in the police force. For many years I have had the opportunity to mix with the upper tiers of society as well as the criminal classes and this has given me great insight into creating my characters and plots.
I love an all-action plot that does not rely on the action to sell the story. This is about artificial intelligence creation and a race to unlock its secret about a murder. There is lots of tech detail and the plot is well thought out.
I loved the fast pace of the story and the main character who is not so much a hero but an ex bad guy who O’Reilly creates beautifully. I do rate this very interesting story about Ai.
'Starts off like a fired bullet and never lets up. A sheer delight' David Baldacci.
At a global tech gala hosted at the British Museum, scientist Tobias Hawke is due to unveil an astonishing breakthrough. His AI system appears to have reached consciousness, making Hawke the leading light in his field.
But when terrorists storm the building, they don't just leave chaos in their wake. They seize Hawke's masterwork, sparking a chain reaction of explosive events which could end the world as we know it.
Michael North, ex-assassin and spy-for-hire, must find the killers and recover the AI. But he…
I was raised in a large family, and we were taught to be respectful, honest, and polite to everyone. I've never been able to understand the mind of a 'nasty' person or how a person can hurt another. When these people are brought to justice, how can we know they are telling the truth?
Expanding on this, I started thinking about Artificial Intelligence—could this be the creation that gives us the way to see into a person's mind; to find out what crime they have committed? But then I thought, what if the actual creator was a criminal? How would anyone even know? That was the route of my research which led to i4Ni being written.
I loved this book with its mix of AI, murder, and mystery. It's about 'accidents' that seem to happen to anyone going against the creator of a predictive AI that they say will be able to anticipate human behaviour.
I liked the fact lots of things happen behind the scenes. An ex-staff member and former coder aims to get to the bottom of it. It looks at the 'what ifs' and throws up the corruption that can happen if there is no strict monitoring in the development of AI.
Again, I feel it brings up the concerns we humans have of the people who will design, build, and operate Artificial Intelligence, and for me, I would want to know who is checking what these companies are actually creating? And who checks the checker...?
This book follows the journey of a writer in search of wisdom as he narrates encounters with 12 distinguished American men over 80, including Paul Volcker, the former head of the Federal Reserve, and Denton Cooley, the world’s most famous heart surgeon.
In these and other intimate conversations, the book…
I have spent over a decade studying and teaching digital media, communication, and technology policy, while also working in journalism and media production. My passion for this topic comes from watching how technology quietly reshapes everyday life, from how people form relationships to how societies govern themselves. I am fascinated by the space where media, culture, and human behavior intersect, especially when change feels invisible but profound. Writing and reading about AI helps me make sense of these transformations, and I care deeply about helping people remain thoughtful, ethical, and human in an increasingly algorithmic world.
I was fascinated by how this book explains the "glitches" in AI as reflections of our own human flaws.
It made me look at my own biases in a whole new way. I love how the author tells stories about the history of technology to show why it is so hard to teach a machine what humans actually value.
Even though the topic sounds technical, I found the writing very conversational and gripping. It felt like reading a detective story where the "mystery" is our own morality. It left me thinking deeply about what it really means to be a "good" person in a world where machines are learning from us and sometime ask us are you human?
Today's "machine-learning" systems, trained by data, are so effective that we've invited them to see and hear for us-and to make decisions on our behalf. But alarm bells are ringing. Recent years have seen an eruption of concern as the field of machine learning advances. When the systems we attempt to teach will not, in the end, do what we want or what we expect, ethical and potentially existential risks emerge. Researchers call this the alignment problem.
Systems cull resumes until, years later, we discover that they have inherent gender biases. Algorithms decide bail and parole-and appear to assess Black…
