Here are 100 books that From Deep Learning to Rational Machines fans have personally recommended if you like
From Deep Learning to Rational Machines.
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I'm passionate about what happens at the seam where creativity meets intelligent machines. My work moves between art, design, and AI, and these books sit on that exact edge. The questions they raise, about consciousness, imagination, alignment, and the honest reckoning with what we build, aren't abstract to me. They're the terrain I work in every day, in the studio and in the workshops I teach.
I think this is one of the most honest books I’ve read on AI.
Russell doesn’t perform gratuitous alarm or sell optimism, he reasons. In my own research and in the workshops I teach on creativity and AI, I’ve spent years around people building systems whose objectives I quietly questioned, and Russell gave me the vocabulary I’d been missing.
I love that he treats control not as a constraint on intelligence but as its precondition and preoccupation. It’s the rare AI book I trust.
A leading artificial intelligence researcher lays out a new approach to AI that will enable us to coexist successfully with increasingly intelligent machines
In the popular imagination, superhuman artificial intelligence is an approaching tidal wave that threatens not just jobs and human relationships, but civilization itself. Conflict between humans and machines is seen as inevitable and its outcome all too predictable.
In this groundbreaking book, distinguished AI researcher Stuart Russell argues that this scenario can be avoided, but only if we rethink AI from the ground up. Russell begins by exploring the idea of intelligence in humans and in machines.…
A moving story of love, betrayal, and the enduring power of hope in the face of darkness.
German pianist Hedda Schlagel's world collapsed when her fiancé, Fritz, vanished after being sent to an enemy alien camp in the United States during the Great War. Fifteen years later, in 1932, Hedda…
Coming from two very different backgrounds gives Dean and I a unique ‘view’ of a topic that we are both hugely passionate about: artificial intelligence. Our work together has gifted us a broader perspective in terms of understanding the development of and the philosophy beneath what is coined as artificial intelligence today and where we truly stand in terms of its potential for good – and evil. Our book list is intended to provide a great starting point from where you can jump into this incredibly absorbing topic and draw your own conclusions about where the future might take us.
As a couple interested in the potential impacts of technology, we were immediately drawn to the question this book poses: "Will technology change what it means to be human?" In 2084, John Lennox addresses this question thoughtfully, offering a perspective grounded in both mathematics and philosophy while incorporating insights from his Christian worldview.
What we found truly compelling about this book was how Lennox draws parallels between the nature of humanity and the possibilities and limitations of AI. He delves into the Christian concept of the soul, our inherent moral sense, and our hopes for the future, effectively highlighting the distinction between machines and human beings.
You don't have to be a computer scientist to have discerning conversations about artificial intelligence and technology. We all wonder where we're headed. Even now, technological innovations and machine learning have a daily impact on our lives, and many of us see good reasons to dread the future. Are we doomed to the surveillance society imagined in George Orwell's 1984?
Mathematician and philosopher John Lennox believes that there are credible answers to the daunting questions that AI poses, and he shows that Christianity has some very serious, sensible, evidence-based responses about…
Coming from two very different backgrounds gives Dean and I a unique ‘view’ of a topic that we are both hugely passionate about: artificial intelligence. Our work together has gifted us a broader perspective in terms of understanding the development of and the philosophy beneath what is coined as artificial intelligence today and where we truly stand in terms of its potential for good – and evil. Our book list is intended to provide a great starting point from where you can jump into this incredibly absorbing topic and draw your own conclusions about where the future might take us.
A fantastic, non-techy read that cuts through the AI fear-mongering in a way that is both hopeful and practical.
The authors work well together to craft a story of how we arrived at this point in time, where our ever-evolving research could lead us, and the practical solutions needed to enable us to move forward in a world governed by the complex and rapidly changing landscape of AI.
The public debut of ChatGPT was a watershed moment. It awakened us to the fact that general artificial intelligence—a technology that had long been a source of fantasy and fiction—was finally here and operating among us. For the first time in history, ordinary citizens could converse directly with an AI chatbot. The thrill of this 'first encounter' with artificial general intelligence, coupled with the astonishing capabilities that AI chatbots displayed, gave rise to concerns about whether AI was sentient or self-aware. Although we have been using AI-assisted applications for years in such forms as facial recognition and language translation, our…
Sine, a professor of creative writing, accompanies Sam, a neuroscientist, on a conference trip to a Hotel Castle. Sam wants to present a new device, the "monitor." Sine hopes to recover from tending to her mother who just passed away.
When they arrive, Sine is in a dream-like state. Real…
Coming from two very different backgrounds gives Dean and I a unique ‘view’ of a topic that we are both hugely passionate about: artificial intelligence. Our work together has gifted us a broader perspective in terms of understanding the development of and the philosophy beneath what is coined as artificial intelligence today and where we truly stand in terms of its potential for good – and evil. Our book list is intended to provide a great starting point from where you can jump into this incredibly absorbing topic and draw your own conclusions about where the future might take us.
We found this book to be an eye-opening exploration of the revolutionary merging of artificial intelligence and biotechnology. Brian Hilbush expertly guided us through the cutting-edge advancements that are transforming drug discovery and therapeutics without being too technical or scientific in his use of language.
We found Hilbush’s story to be a fascinating breakdown of how AI and deep learning are revolutionizing medicine, with some great insights into the rise of data science in healthcare, groundbreaking biotech innovations, and the exciting startup landscape shaping the industry's future.
Learn how AI and data science are upending the worlds of biology and medicine
In Silico Dreams: How Artificial Intelligence and Biotechnology Will Create the Medicines of the Future delivers an illuminating and fresh perspective on the convergence of two powerful technologies: AI and biotech. Accomplished genomics expert, executive, and author Brian Hilbush offers readers a brilliant exploration of the most current work of pioneering tech giants and biotechnology startups who have already started disrupting healthcare. The book provides an in-depth understanding of the sources of innovation that are driving the shift in the pharmaceutical industry away from serendipitous therapeutic…
I’ve been a geeky kid all my life. (I don’t think I’ve quite grown up yet.) Born in the 1970s, my childhood was a wonderful playground of building robots and software. I was awarded one of the early degrees in AI, and a PhD in genetic algorithms. I’ve since spent 25 years exploring how to make computers think, build, invent, compose… and I’ve also spent 20 years writing popular science books. I’m lucky enough to be a Professor in one of the world’s best universities for Computer Science and Machine Learning: UCL, and I guess I’ve written two or three hundred scientific papers over the years. I still think I know nothing at all about real or artificial intelligence, but then does anyone?
I’ve not met Harry, but he seems to have a logical and sensible head on his shoulders. His writing is considered and grounded, which is exactly what you need when discussing the hype that forever seems to surround AI. This book is another look at this topic and finds yet more ways to explain to readers the difference between human intelligence and our algorithmic attempts at intelligence – which are frequently pretty stupid.
Recent startling successes in machine intelligence using a technique called 'deep learning' seem to blur the line between human and machine as never before. Are computers on the cusp of becoming so intelligent that they will render humans obsolete? Harry Collins argues we are getting ahead of ourselves, caught up in images of a fantastical future dreamt up in fictional portrayals. The greater present danger is that we lose sight of the very real limitations of artificial intelligence and readily enslave ourselves to stupid computers: the 'Surrender'.
By dissecting the intricacies of language use and meaning, Collins shows how far…
I became fascinated by the highest achievements of human intelligence while a graduate student in philosophy working on the discovery and justification of scientific theories. Shortly after I got my PhD, I started working with cognitive psychologists who gave me an appreciation for empirical studies of intelligent thinking. Psychology led me to computational modeling of intelligence and I learned to build my own models. Much later a graduate student got me interested in questions about intelligence in non-human animals. After teaching a course on intelligence in machines, humans, and other animals, I decided to write a book that provides a systematic comparison: Bots and Beasts.
This book provides a good introduction to the current state of machine intelligence through interviews with many leading practitioners including Geoffrey Hinton, Yann LeCun, Stuart Russell, and Demis Hassabis (DeepMind). You will get a sense of both of AI’s recent accomplishments and how far it falls short of full human intelligence.
How will AI evolve and what major innovations are on the horizon? What will its impact be on the job market, economy, and society? What is the path toward human-level machine intelligence? What should we be concerned about as artificial intelligence advances?
Architects of Intelligence contains a series of in-depth, one-to-one interviews where New York Times bestselling author, Martin Ford, uncovers the truth behind these questions from some of the brightest minds in the Artificial Intelligence community.
Martin has wide-ranging conversations with twenty-three…
In an age of splendor, a heretic king strips Egypt bare—forcing his queen to quell rebellion and plunging his children into a conspiracy against the crown.
Salvation in the Sun follows Nefertiti as she ascends the throne beside Pharaoh Amenhotep—soon to become Akhenaten—just as he declares war on Egypt’s ancient…
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…
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.
While it’s not the newest tech, I love that it covers the essential groundwork that sparked the modern AI revolution. I personally think its perfect for engineers and data scientists. It's also a great precursor to my book, giving you the strong foundation you need before diving into the next wave of AI advancements.
Generative modeling is one of the hottest topics in AI. It's now possible to teach a machine to excel at human endeavors such as painting, writing, and composing music. With this practical book, machine-learning engineers and data scientists will discover how to re-create some of the most impressive examples of generative deep learning models, such as variational autoencoders,generative adversarial networks (GANs), encoder-decoder models and world models.
Author David Foster demonstrates the inner workings of each technique, starting with the basics of deep learning before advancing to some of the most cutting-edge algorithms in the field. Through tips and tricks, you'll…
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…
Born the heir of a master woodcutter in a queendom defined by guilds and matrilineal inheritance, nonbinary Sorin can’t quite seem to find their place. At seventeen, an opportunity to attend an alchemical guild fair and secure an apprenticeship with the…
I build and use emerging technological innovations in business, and I also teach others how they might too! I’m a serial entrepreneur and a Professor at the Wharton School of the University of Pennsylvania. As an entrepreneur, I co-founded and developed the core IP for Yodle Inc, a venture-backed firm that was acquired by Web.com. I’m now the founder of Jumpcut Media – a startup using data and Web3 technologies to democratize opportunities in Film and TV. In all this work, I'm often trying to assess how emerging technologies may affect business and society in the long run and how I can apply them to create new products and services.
This book provides an excellent description of the various kinds of machine learning approaches and asks the question of whether there will be a Master Algorithm, one single (universal) algorithm that learns all kinds of tasks from data. The author, Pedro Domingos, introduces the different approaches to building intelligence and the research tribes exploring them – Symbolists (with its foundations in Philosophy and Logic), Connectionists (foundations in Neuro/Cognitive Science), Evolutionaries (foundations in Evolutionary Biology), Bayesians (statistical foundations), and Analogizers (Psychology). He also introduces some of his own ideas on what the master machine learning algorithm might look like. It’s a really useful primer for those who are not deeply immersed in machine learning but it’s written for readers with at least a basic engineering and computer science background.
Algorithms increasingly run our lives. They find books, movies, jobs, and dates for us, manage our investments, and discover new drugs. More and more, these algorithms work by learning from the trails of data we leave in our newly digital world. Like curious children, they observe us, imitate, and experiment. And in the world's top research labs and universities, the race is on to invent the ultimate learning algorithm: one capable of discovering any knowledge from data, and doing anything we want, before we even ask.Machine learning is the automation of discovery,the scientific method on steroids,that enables intelligent robots and…
