T-Minus AI


Book Description

Late in 2017, the global significance of the conversation about artificial intelligence (AI) changed forever. China put the world on alert when it released a plan to dominate all aspects of AI across the planet. Only weeks later, Vladimir Putin raised a Russian red flag in response by declaring AI the future for all humankind, and proclaiming that, "Whoever becomes the leader in this sphere will become the ruler of the world." The race was on. Consistent with their unique national agendas, countries throughout the world began plotting their paths and hurrying their pace. Now, not long after, the race has become a sprint. Despite everything at stake, to most of us AI remains shrouded by a cloud of mystery and misunderstanding. Hidden behind complicated and technical jargon and confused by fantastical depictions of science fiction, the modern realities of AI and its profound implications are hard to decipher, but crucial to recognize. In T-Minus AI: Humanity's Countdown to Artificial Intelligence and the New Pursuit of Global Power, author Michael Kanaan explains AI from a human-oriented perspective we can all finally understand. A recognized national expert and the U.S. Air Force's first Chairperson for Artificial Intelligence, Kanaan weaves a compelling new view on our history of innovation and technology to masterfully explain what each of us should know about modern computing, AI, and machine learning. Kanaan also dives into the global implications of AI by illuminating the cultural and national vulnerabilities already exposed and the pressing issues now squarely on the table. AI has already become China's all-purpose tool to impose its authoritarian influence around the world. Russia, playing catch up, is weaponizing AI through its military systems and now infamous, aggressive efforts to disrupt democracy by whatever disinformation means possible. America and like-minded nations are awakening to these new realities—and the paths they're electing to follow echo loudly the political foundations and, in most cases, the moral imperatives upon which they were formed. As we march toward a future far different than ever imagined, T-Minus AI is fascinating and crucially well-timed. It leaves the fiction behind, paints the alarming implications of AI for what they actually are, and calls for unified action to protect fundamental human rights and dignities for all.




T-Minus


Book Description

In graphic novel format, presents the story of two world superpowers racing to land a man on the moon, and the people who worked on the project.




Doing AI


Book Description

Artificial intelligence (AI) has captured our imaginations—and become a distraction. Too many leaders embrace the oversized narratives of artificial minds outpacing human intelligence and lose sight of the original problems they were meant to solve. When businesses try to “do AI,” they place an abstract solution before problems and customers without fully considering whether it is wise, whether the hype is true, or how AI will impact their organization in the long term. Often absent is sound reasoning for why they should go down this path in the first place. Doing AI explores AI for what it actually is—and what it is not— and the problems it can truly solve. In these pages, author Richard Heimann unravels the tricky relationship between problems and high-tech solutions, exploring the pitfalls in solution-centric thinking and explaining how businesses should rethink AI in a way that aligns with their cultures, goals, and values. As the Chief AI Officer at Cybraics Inc., Richard Heimann knows from experience that AI-specific strategies are often bad for business. Doing AI is his comprehensive guide that will help readers understand AI, avoid common pitfalls, and identify beneficial applications for their companies. This book is a must-read for anyone looking for clarity and practical guidance for identifying problems and effectively solving them, rather than getting sidetracked by a shiny new “solution” that doesn’t solve anything.




The AI Does Not Hate You


Book Description

A deep-dive into the weird and wonderful world of Artificial Intelligence. 'The AI does not hate you, nor does it love you, but you are made of atoms which it can use for something else'. This is a book about AI and AI risk. But it's also more importantly about a community of people who are trying to think rationally about intelligence, and the places that these thoughts are taking them, and what insight they can and can't give us about the future of the human race over the next few years. It explains why these people are worried, why they might be right, and why they might be wrong. It is a book about the cutting edge of our thinking on intelligence and rationality right now by the people who stay up all night worrying about it. Along the way, we discover why we probably don't need to worry about a future AI resurrecting a perfect copy of our minds and torturing us for not inventing it sooner, but we perhaps should be concerned about paperclips destroying life as we know it; how Mickey Mouse can teach us an important lesson about how to program AI; and how a more rational approach to life could be what saves us all. --




The Five Forces That Change Everything


Book Description

The Five Forces reveals how technology is unleashing forces that will forever alter our lives, politics, and society. Learn more about nanotechnology, transhumanism, the future of space exploration and colonization, super human computers, and so much more! Discover what lies in our future: How will humans change as we merge with our machines, embracing transhumanism? What happens when intelligent algorithms make all the decisions? Should we connect our brains directly to the Internet? And are we entering an age of simulated realities? The Five Forces takes you on a journey to see what the most brilliant minds of our age are dreaming up. Hoffman reveals how new scientific breakthroughs and business ventures are poised to reshape our lives and turn science fiction into fact. With scientists in Japan creating humanoid robots, Silicon Valley biohackers boosting their IQs, and Chinese labs developing human-monkey chimeras, Hoffman gives an inside look at the limits of what’s possible today and the impact these developments will have. Mass Connectivity What happens when brain chips connect our minds directly to the internet? Will we be able to boost our IQs, exchange memories, and communicate with our thoughts? Or will this turn into a nightmare, with corporations reading our minds, hackers overwriting our identities, and governments controlling our actions? Bio Convergence Now that we can decode the building blocks of life and create new lifeforms that never existed before, what comes next? Will we conquer disease, resurrect extinct species, develop superior plants and animals, create DNA-edited babies, and even spawn other intelligent beings? Human Expansionism Is it our manifest destiny to colonize Mars and extend the human race beyond the limits of our solar system? How will technologies like space travel, new materials, and nanotech transform our civilization and open up new horizons we never imagined possible? Deep Automation As our machines become capable enough to do every job better, faster, and cheaper, how will this affect society? Will we wind up delegating our most important decisions to data crunching algorithms? And does this mean our machines will end up running our economies, our corporations, and even our lives? Intelligence Explosion As soon as we create a superintelligence that far surpasses human capabilities, what will happen to us? Will we be able to control our machines, or will they eventually control us? Are we headed for a paradise of plenty, where our technology eliminates hunger, disease, poverty, and war? Or will this be the end of our reign as the rulers of the planet?




The Creativity Code


Book Description

“A brilliant travel guide to the coming world of AI.” —Jeanette Winterson What does it mean to be creative? Can creativity be trained? Is it uniquely human, or could AI be considered creative? Mathematical genius and exuberant polymath Marcus du Sautoy plunges us into the world of artificial intelligence and algorithmic learning in this essential guide to the future of creativity. He considers the role of pattern and imitation in the creative process and sets out to investigate the programs and programmers—from Deep Mind and the Flow Machine to Botnik and WHIM—who are seeking to rival or surpass human innovation in gaming, music, art, and language. A thrilling tour of the landscape of invention, The Creativity Code explores the new face of creativity and the mysteries of the human code. “As machines outsmart us in ever more domains, we can at least comfort ourselves that one area will remain sacrosanct and uncomputable: human creativity. Or can we?...In his fascinating exploration of the nature of creativity, Marcus du Sautoy questions many of those assumptions.” —Financial Times “Fascinating...If all the experiences, hopes, dreams, visions, lusts, loves, and hatreds that shape the human imagination amount to nothing more than a ‘code,’ then sooner or later a machine will crack it. Indeed, du Sautoy assembles an eclectic array of evidence to show how that’s happening even now.” —The Times




The Centaur's Dilemma


Book Description

Assessing the legal and practical questions posed by the use of artificial intelligence in national security matters The increasing use of artificial intelligence poses challenges and opportunities for nearly all aspects of society, including the military and other elements of the national security establishment. This book addresses how national security law can and should be applied to artificial intelligence, which enables a wide range of decisions and actions not contemplated by current law. James Baker, an expert in national security law and process, adopts a realistic approach in assessing how the law—even when not directly addressing artificial intelligence—can be used, or even misused, to regulate this new technology. His new book covers, among other topics, national security process, constitutional law, the law of armed conflict, arms control, and academic and corporate ethics. With his own background as a judge, he examines potential points of contention and litigation in an area where the law is still evolving and might not yet provide clear and certain answers. The Centaur's Dilemma also analyzes potential risks associated with the use of artificial intelligence in the realm of national security—including the challenges of machine-human interface, operating (or not operating) the national-security decision-making process at machine speed, and the perils of a technology arms race. Written in plain English, The Centaur's Dilemma will help guide policymakers, lawyers, and technology experts as they deal with the many legal questions that will arise when using artificial intelligence to plan and carry out the actions required for the nation's defense.




Rebooting AI


Book Description

Two leaders in the field offer a compelling analysis of the current state of the art and reveal the steps we must take to achieve a truly robust artificial intelligence. Despite the hype surrounding AI, creating an intelligence that rivals or exceeds human levels is far more complicated than we have been led to believe. Professors Gary Marcus and Ernest Davis have spent their careers at the forefront of AI research and have witnessed some of the greatest milestones in the field, but they argue that a computer beating a human in Jeopardy! does not signal that we are on the doorstep of fully autonomous cars or superintelligent machines. The achievements in the field thus far have occurred in closed systems with fixed sets of rules, and these approaches are too narrow to achieve genuine intelligence. The real world, in contrast, is wildly complex and open-ended. How can we bridge this gap? What will the consequences be when we do? Taking inspiration from the human mind, Marcus and Davis explain what we need to advance AI to the next level, and suggest that if we are wise along the way, we won't need to worry about a future of machine overlords. If we focus on endowing machines with common sense and deep understanding, rather than simply focusing on statistical analysis and gatherine ever larger collections of data, we will be able to create an AI we can trust—in our homes, our cars, and our doctors' offices. Rebooting AI provides a lucid, clear-eyed assessment of the current science and offers an inspiring vision of how a new generation of AI can make our lives better.




Hands-On Explainable AI (XAI) with Python


Book Description

Resolve the black box models in your AI applications to make them fair, trustworthy, and secure. Familiarize yourself with the basic principles and tools to deploy Explainable AI (XAI) into your apps and reporting interfaces. Key FeaturesLearn explainable AI tools and techniques to process trustworthy AI resultsUnderstand how to detect, handle, and avoid common issues with AI ethics and biasIntegrate fair AI into popular apps and reporting tools to deliver business value using Python and associated toolsBook Description Effectively translating AI insights to business stakeholders requires careful planning, design, and visualization choices. Describing the problem, the model, and the relationships among variables and their findings are often subtle, surprising, and technically complex. Hands-On Explainable AI (XAI) with Python will see you work with specific hands-on machine learning Python projects that are strategically arranged to enhance your grasp on AI results analysis. You will be building models, interpreting results with visualizations, and integrating XAI reporting tools and different applications. You will build XAI solutions in Python, TensorFlow 2, Google Cloud’s XAI platform, Google Colaboratory, and other frameworks to open up the black box of machine learning models. The book will introduce you to several open-source XAI tools for Python that can be used throughout the machine learning project life cycle. You will learn how to explore machine learning model results, review key influencing variables and variable relationships, detect and handle bias and ethics issues, and integrate predictions using Python along with supporting the visualization of machine learning models into user explainable interfaces. By the end of this AI book, you will possess an in-depth understanding of the core concepts of XAI. What you will learnPlan for XAI through the different stages of the machine learning life cycleEstimate the strengths and weaknesses of popular open-source XAI applicationsExamine how to detect and handle bias issues in machine learning dataReview ethics considerations and tools to address common problems in machine learning dataShare XAI design and visualization best practicesIntegrate explainable AI results using Python modelsUse XAI toolkits for Python in machine learning life cycles to solve business problemsWho this book is for This book is not an introduction to Python programming or machine learning concepts. You must have some foundational knowledge and/or experience with machine learning libraries such as scikit-learn to make the most out of this book. Some of the potential readers of this book include: Professionals who already use Python for as data science, machine learning, research, and analysisData analysts and data scientists who want an introduction into explainable AI tools and techniquesAI Project managers who must face the contractual and legal obligations of AI Explainability for the acceptance phase of their applications




PyTorch 1.x Reinforcement Learning Cookbook


Book Description

Implement reinforcement learning techniques and algorithms with the help of real-world examples and recipes Key FeaturesUse PyTorch 1.x to design and build self-learning artificial intelligence (AI) modelsImplement RL algorithms to solve control and optimization challenges faced by data scientists todayApply modern RL libraries to simulate a controlled environment for your projectsBook Description Reinforcement learning (RL) is a branch of machine learning that has gained popularity in recent times. It allows you to train AI models that learn from their own actions and optimize their behavior. PyTorch has also emerged as the preferred tool for training RL models because of its efficiency and ease of use. With this book, you'll explore the important RL concepts and the implementation of algorithms in PyTorch 1.x. The recipes in the book, along with real-world examples, will help you master various RL techniques, such as dynamic programming, Monte Carlo simulations, temporal difference, and Q-learning. You'll also gain insights into industry-specific applications of these techniques. Later chapters will guide you through solving problems such as the multi-armed bandit problem and the cartpole problem using the multi-armed bandit algorithm and function approximation. You'll also learn how to use Deep Q-Networks to complete Atari games, along with how to effectively implement policy gradients. Finally, you'll discover how RL techniques are applied to Blackjack, Gridworld environments, internet advertising, and the Flappy Bird game. By the end of this book, you'll have developed the skills you need to implement popular RL algorithms and use RL techniques to solve real-world problems. What you will learnUse Q-learning and the state–action–reward–state–action (SARSA) algorithm to solve various Gridworld problemsDevelop a multi-armed bandit algorithm to optimize display advertisingScale up learning and control processes using Deep Q-NetworksSimulate Markov Decision Processes, OpenAI Gym environments, and other common control problemsSelect and build RL models, evaluate their performance, and optimize and deploy themUse policy gradient methods to solve continuous RL problemsWho this book is for Machine learning engineers, data scientists and AI researchers looking for quick solutions to different reinforcement learning problems will find this book useful. Although prior knowledge of machine learning concepts is required, experience with PyTorch will be useful but not necessary.