When it comes to what we believe, humans see what they want to see. In other words, we have what Julia Galef calls a "soldier" mindset. From tribalism and wishful thinking, to rationalizing in our personal lives and everything in between, we are driven to defend the ideas we most want to believe - and shoot down those we don't. 

In Artificial Intelligence, Mitchell turns to the most urgent questions concerning AI today: How intelligent - really - are the best AI programs? How do they work? What can they actually do, and when do they fail? How humanlike do we expect them to become, and how soon do we need to worry about them surpassing us? Along the way, she introduces the dominant methods of modern AI and machine learning, describing cutting-edge AI programs, their human inventors, and the historical lines of thought that led to recent achievements.  

This urgent and eye-opening book makes the case that protecting humanity's future is the central challenge of our time. If all goes well, human history is just beginning. Our species could survive for billions of years - enough time to end disease, poverty, and injustice, and to flourish in ways unimaginable today. But this vast future is at risk. With the advent of nuclear weapons, humanity entered a new age, where we face existential catastrophes - those from which we could never come back.

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 all of neuroscience's advances, we've made little progress on its biggest question: How do simple cells in the brain create intelligence? Jeff Hawkins and his team discovered that the brain uses map-like structures to build a model of the world - not just one model, but hundreds of thousands of models of everything we know. This discovery allows Hawkins to answer important questions about how we perceive the world, why we have a sense of self, and the origin of high-level thought. 

Deep Learning with Python introduces the field of deep learning using the Python language and the powerful Keras library. Written by Keras creator and Google AI researcher François Chollet, this audiobook builds your understanding through intuitive explanations and practical examples. You'll explore challenging concepts and practice with applications in computer vision, natural-language processing, and generative models. By the time you finish, you'll have the knowledge and hands-on skills to apply deep learning in your own projects.  

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.

When it comes to what we believe, humans see what they want to see. In other words, we have what Julia Galef calls a 'soldier' mindset. From tribalism and wishful thinking, to rationalising in our personal lives and everything in between, we are driven to defend the ideas we most want to believe—and shoot down those we don't. But if we want to get things right more often we should train ourselves to think more like a scout. 

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.

One of our great contemporary scientists reveals the 10 profound insights that illuminate what everyone should know about the physical world. 

Max Tegmark leads us on an astonishing journey through past, present and future, and through the physics, astronomy, and mathematics that are the foundation of his work, most particularly his hypothesis that our physical reality is a mathematical structure and his theory of the ultimate multiverse. In a dazzling combination of both popular and groundbreaking science, he not only helps us grasp his often mind-boggling theories, but he also shares with us some of the often surprising triumphs and disappointments that have shaped his life as a scientist.

The term machine learning refers to the capability of a machine to learn something without any pre-existing program. Automatic learning is a way to educate an algorithm to learn from various environmental situations. Machine learning involves the usage of enormous quantities of data and an efficient algorithm enabled to adapt and enhance its capabilities according to recurring situations. From banking operations to online shopping and also on social media, we daily use machine learning data algorithms to make our experience more efficient, simple and secure.

This audiobook is about luck, or more precisely, how we perceive and deal with luck in life and business. It is already a landmark work, and its title has entered our vocabulary. In its second edition, Fooled by Randomness is now a cornerstone for anyone interested in random outcomes.

Recently many people have assumed that we are blank slates shaped by our environment. But this denies the heart of our being: human nature. Violence is not just a product of society; male and female minds are different; the genes we give our children shape them more than our parenting practices. To acknowledge our innate abilities, Pinker shows, is not to condone inequality but to understand the very foundations of humanity. 

Grokking Simplicity is a friendly, practical guide that will change the way you approach software design and development. Distributed across servers, difficult to test, and resistant to modification - modern software is complex. Grokking Simplicity is a friendly, practical guide that will change the way you approach software design and development. It introduces a unique approach to functional programming that explains why certain features of software are prone to complexity, and teaches you the functional techniques you can use to simplify these systems.