Futurists insist that AI will soon eclipse the capacities of the most gifted human mind. What hope do we have against superintelligent machines? But we aren't really on the path to developing intelligent machines. In fact, we don't even know where that path might be. Erik Larson takes us on a tour of the landscape of AI to show how far we are from superintelligence and what it would take to get there.

We are approaching a critical threshold in the history of our species. Soon you will live surrounded by AIs. They will organize your life, operate your business, and run core government services. You will live in a world of DNA printers and quantum computers, engineered pathogens and autonomous weapons, robot assistants and abundant energy. None of us are prepared. As co-founder of the pioneering AI company DeepMind, Mustafa Suleyman has been at the center of this revolution. The coming decade, he argues, will be defined by this wave of powerful, fast-proliferating new technologies.

An explosive, completely new understanding of heat, the lethal force which threatens every living cell on Earth. New York Times best-selling journalist Jeff Goodell presents a searing examination of the impact that temperature rise will have on our lives and on our planet, offering a vital new perspective on where we are headed, how we can prepare, and what is at stake if we fail to act.

Everyone would benefit from seeing further into the future, whether buying stocks, crafting policy, launching a new product, or simply planning the week's meals. Unfortunately, people tend to be terrible forecasters. As Wharton professor Philip Tetlock showed in a landmark 2005 study, even experts' predictions are only slightly better than chance. However, an important and underreported conclusion of that study was that some experts do have real foresight.

Learning data analytics will open up new opportunities for you. Data analytics will be the most in-demand skill by 2030. Right now, the higher the data literacy the employee has the higher the salary he can get, for example in the US employees with solid data analytics knowledge can increase their annual salary by $11,000. (source: QLIK Technologies, Inc.)

Totalitarianism is not a coincidence and does not form in a vacuum. It arises from a collective psychosis that has followed a predictable script throughout history. In The Psychology of Totalitarianism, world-renowned Professor of Clinical Psychology Mattias Desmet deconstructs the societal conditions that allow this collective psychosis to take hold. By looking at our current situation and identifying the phenomenon of “mass formation”—a type of collective hypnosis—he clearly illustrates how close we are to surrendering to totalitarian regimes.

Do you know how to build a machine learning algorithm in Python? Have you learned how to build a neural network in Python? If you have listened to the first three audiobooks in the series, you will know how to do both those things. If you want to learn more about the concepts related to machine learning and some subjects and concepts that are linked to machine learning, you have come to the right place.

From the best-selling author of Thinking, Fast and Slow, the co-author of Nudge, and the author of You Are About to Make a Terrible Mistake! comes Noise, a revolutionary exploration of why people make bad judgments, and how to control both noise and cognitive bias.

Are you thinking about learning data science? Do you know how to code in Python and want to take your learning further? Data is more available today than it ever has been and in much larger quantities than ever before. And it's only set to increase. Because of that, we need to evolve in how we process data, and that's where data science comes in. But let's not forget machine learning, a subset of data science that offers us ways of examining and analyzing data to draw meaningful insights.

Superintelligence asks the questions: What happens when machines surpass humans in general intelligence? Will artificial agents save or destroy us? Nick Bostrom lays the foundation for understanding the future of humanity and intelligent life. The human brain has some capabilities that the brains of other animals lack. It is to these distinctive capabilities that our species owes its dominant position. If machine brains surpassed human brains in general intelligence, then this new superintelligence could become extremely powerful - possibly beyond our control.

Under the aegis of machine learning in our data-driven machine age, computers are programming themselves and learning about - and solving - an extraordinary range of problems, from the mundane to the most daunting. Today it is machine learning programs that enable Amazon and Netflix to predict what users will like, Apple to power Siri's ability to understand voices, and Google to pilot cars.

For over three decades, Ray Kurzweil has been one of the most respected and provocative advocates of the role of technology in our future. In his classic The Age of Spiritual Machines, he argued that computers would soon rival the full range of human intelligence at its best. Now he examines the next step in this inexorable evolutionary process: The union of human and machine, in which the knowledge and skills embedded in our brains will be combined with the vastly greater capacity, speed, and knowledge-sharing ability of our creations.

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 audiobook, 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.

This book is designed to be an introduction to machine learning algorithms for a complete beginner. It starts with an explanation of exactly what machine learning algorithms are and then walks you through the languages and frameworks used to create them. Studying machine learning is considered to be quite challenging due to the impression that special talent is required or some unachievable level of mathematics is needed in order to understand the various algorithms and techniques. But anyone can learn to become a machine learner and put the theory into practice.

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. Systems cull résumés until, years later, we discover that they have inherent gender biases. Algorithms decide bail and parole - and appear to assess black and white defendants differently. We can no longer assume that our mortgage application, or even our medical tests, will be seen by human eyes. And autonomous vehicles on our streets can injure or kill.

Under the aegis of machine learning in our data-driven machine age, computers are programming themselves and learning about - and solving - an extraordinary range of problems, from the mundane to the most daunting. Today it is machine learning programs that enable Amazon and Netflix to predict what users will like, Apple to power Siri's ability to understand voices, and Google to pilot cars.

As we use the Web for social networking, shopping, and news, we leave a personal trail. These days, linger over a Web page selling lamps, and they will turn up at the advertising margins as you move around the Internet, reminding you, tempting you to make that purchase. Search engines such as Google can now look deep into the data on the Web to pull out instances of the words you are looking for. And there are pages that collect and assess information to give you a snapshot of changing political opinion.

Jeff Hawkins, the man who created the PalmPilot, Treo smart phone, and other handheld devices, has reshaped our relationship to computers. Now he stands ready to revolutionize both neuroscience and computing in one stroke, with a new understanding of intelligence itself.

When most of us think about artificial intelligence, our minds go straight to cyborgs, robots, and sci-fi thrillers where machines take over the world. But the truth is that artificial intelligence is already among us. It exists in our smartphones, fitness trackers, and refrigerators that tell us when the milk will expire. In some ways the future people dreamed of at the World's Fair in the 1960s is already here. We're teaching our machines how to think like humans, and they're learning at an incredible rate.

Many people today are so dazzled by the long-term potential for artificial intelligence that they overlook the much clearer and more immediate potential for a new form of "collective intelligence": the intelligence of groups of people and computers working together. In Superminds, Thomas Malone explains what we need to do to take advantage of this potential. Groundbreaking and utterly fascinating, Superminds will change the way you work - both with others and with computers - for the better.

Over a storied career, Daniel C. Dennett has engaged questions about science and the workings of the mind. His answers have combined rigorous argument with strong empirical grounding. And a lot of fun. Intuition Pumps and Other Tools for Thinking offers seventy-seven of Dennett’s most successful “imagination-extenders and focus-holders” meant to guide you through some of life’s most treacherous subject matter: evolution, meaning, mind, and free will.

The Great Mental Models: General Thinking Concepts is the first book in The Great Mental Models series designed to upgrade your thinking with the best, most useful and powerful tools so you always have the right one on hand. This volume details nine of the most versatile all-purpose mental models you can use right away to improve your decision making, your productivity, and how clearly you see the world.

What is economic growth? And why, historically, has it occurred in only a few places? Previous efforts to answer these questions have focused on institutions, geography, finances, and psychology. But according to MIT's anti-disciplinarian César Hidalgo, understanding the nature of economic growth demands transcending the social sciences and including the natural sciences of information, networks, and complexity. To understand the growth of economies, Hidalgo argues, we first need to understand the growth of order.

In Mind in Motion, psychologist Barbara Tversky shows that spatial cognition isn't just a peripheral aspect of thought, but its very foundation, enabling us to draw meaning from our bodies and their actions in the world. Our actions in real space get turned into mental actions on thought, often spouting spontaneously from our bodies as gestures. Spatial thinking underlies creating and using maps, assembling furniture, devising football strategies, designing airports, understanding the flow of people, traffic, water, and ideas.

Can there be freedom and free will in a deterministic world? Renowned philosopher Daniel Dennett emphatically answers "yes!" Using an array of provocative formulations, Dennett sets out to show how we alone among the animals have evolved minds that give us free will and morality. Weaving a richly detailed narrative, Dennett explains in a series of strikingly original arguments - drawing upon evolutionary biology, cognitive neuroscience, economics, and philosophy - that far from being an enemy of traditional explorations of freedom, morality, and meaning, the evolutionary perspective can be an indispensable ally.

Throughout his distinguished and unconventional career, engineer-turned-molecular-biologist Douglas Axe has been asking the questions that much of the scientific community would rather silence. Now, he presents his conclusions in this brave and pioneering book. Axe argues that the key to understanding our origin is the "design intuition" - the innate belief held by all humans that tasks we would need knowledge to accomplish can be accomplished only by someone who has that knowledge.

Consciousness is our gateway to experience: it enables us to recognize Van Gogh’s starry skies, be enraptured by Beethoven’s Fifth, and stand in awe of a snowcapped mountain. Yet consciousness is subjective, personal, and famously difficult to examine: philosophers have for centuries declared this mental entity so mysterious as to be impenetrable to science. In The Ravenous Brain, neuroscientist Daniel Bor departs sharply from this historical view, and proposes a new model for how consciousness works.

K. Eric Drexler is the founding father of nanotechnology - the science of engineering on a molecular level. In Radical Abundance, he shows how rapid scientific progress is about to change our world. Thanks to atomically precise manufacturing, we will soon have the power to produce radically more of what people want, and at a lower cost. The result will shake the very foundations of our economy and environment.

We are living in a world in which cows send texts to farmers when they're in heat, where the most valuable real estate in New York City houses computers, not people, and some of humanity's greatest works are created by crowds, not individuals. We are in the midst of a networking revolution - set to transform the way we access the world's information and the way we connect with one another. Studying biological systems is perhaps the best way to understand such networks, and nature has a lesson for us if we care to listen: Bigger is rarely better in the long run.

A fascinating guided tour of the complex, fast-moving, and influential world of algorithms - what they are, why they’re such powerful predictors of human behavior, and where they’re headed next. Algorithms exert an extraordinary level of influence on our everyday lives - from dating websites and financial trading floors, through to online retailing and internet searches - Google's search algorithm is now a more closely guarded commercial secret than the recipe for Coca-Cola.

Artificial intelligence touches nearly every part of your day. While you may initially assume that technology such as smart speakers and digital assistants are the extent of it, AI has in fact rapidly become a general-purpose technology, reverberating across industries including transportation, healthcare, financial services, and many more. In our modern era, an understanding of AI and its possibilities for your organization is essential for growth and success. Artificial Intelligence Basics has arrived to equip you with a fundamental, timely grasp of AI and its impact. 

ChatGPT For Dummies demystifies the artificial intelligence tool that can answer questions, write essays, and generate just about any kind of text it's asked for. This powerful example of generative AI is widely predicted to upend education and business. In this book, you'll learn how ChatGPT works and how you can operate it in a way that yields satisfactory results. You'll also explore the ethics of using AI-generated content for various purposes.

In AI Superpowers, Kai-fu Lee argues powerfully that because of these unprecedented developments in AI, dramatic changes will be happening much sooner than many of us expected. Indeed, as the US-Sino AI competition begins to heat up, Lee urges the US and China to both accept and to embrace the great responsibilities that come with significant technological power.

AI will be the defining development of the 21st century. Within two decades, aspects of daily human life will be unrecognizable. AI will generate unprecedented wealth, revolutionize medicine and education through human-machine symbiosis, and create brand-new forms of communication and entertainment. In liberating us from routine work, however, AI will also challenge the organizing principles of our economic and social order.

How will artificial intelligence affect crime, war, justice, jobs, society, and our very sense of being human? The rise of AI has the potential to transform our future more than any other technology - and there's nobody better qualified or situated to explore that future than Max Tegmark, an MIT professor who's helped mainstream research on how to keep AI beneficial.