Art Intelligence

“A lively account . . . combines the derring-do of old-fashioned spycraft with thoughtful meditations on the future of warfare and intelligence work. It deserves to be read.” —The Washington Post “Offer[s] an exceptionally deep glimpse into the CIA’s counterterrorism operations in the last decade of the twentieth century.” —Harper’s A legendary CIA spy and counterterrorism expert tells the spellbinding story of his high-risk, action-packed career Revelatory and groundbreaking, The Art of Intelligence will change the way people view the CIA, domestic and foreign intelligence, and international terrorism. Henry A. “Hank” Crumpton, a twenty-four-year veteran of the CIA’s Clandestine Service, offers a thrilling account that delivers profound lessons about what it means to serve as an honorable spy. From CIA recruiting missions in Africa to pioneering new programs like the UAV Predator, from running post–9/11 missions in Afghanistan to heading up all clandestine CIA operations in the United States, Crumpton chronicles his role—in the battlefield and in the Oval Office—in transforming the way America wages war and sheds light on issues of domestic espionage.

Artists always react to the times in which they live. They may celebrate them or criticize them, often trying to change them. But this is the first time in history that technology controlled by private companies is offering to replace the work of writers, musicians, illustrators and visual artists. What impact will generative AI have on how we create art and how we understand what art is for? How will it affect the role of the artist in the future and the conditions under which artists will work? Jan Svenungsson tackles these questions, investigating what AI might do for art, and what it might change, circling the core issue of what it is in human art-making that cannot be replaced.

An engrossing guide to seeing—and communicating—more clearly from the groundbreaking course that helps FBI agents, cops, CEOs, ER docs, and others save money, reputations, and lives. How could looking at Monet’s water lily paintings help save your company millions? How can checking out people’s footwear foil a terrorist attack? How can your choice of adjective win an argument, calm your kid, or catch a thief? In her celebrated seminar, the Art of Perception, art historian Amy Herman has trained experts from many fields how to perceive and communicate better. By showing people how to look closely at images, she helps them hone their “visual intelligence,” a set of skills we all possess but few of us know how to use properly. She has spent more than a decade teaching doctors to observe patients instead of their charts, helping police officers separate facts from opinions when investigating a crime, and training professionals from the FBI, the State Department, Fortune 500 companies, and the military to recognize the most pertinent and useful information. Her lessons highlight far more than the physical objects you may be missing; they teach you how to recognize the talents, opportunities, and dangers that surround you every day. Whether you want to be more effective on the job, more empathetic toward your loved ones, or more alert to the trove of possibilities and threats all around us, this book will show you how to see what matters most to you more clearly than ever before. Please note: this ebook contains full-color art reproductions and photographs, and color is at times essential to the observation and analysis skills discussed in the text. For the best reading experience, this ebook should be viewed on a color device.

Neuro-symbolic AI is an emerging subfield of Artificial Intelligence that brings together two hitherto distinct approaches. ”Neuro” refers to the artificial neural networks prominent in machine learning, ”symbolic” refers to algorithmic processing on the level of meaningful symbols, prominent in knowledge representation. In the past, these two fields of AI have been largely separate, with very little crossover, but the so-called “third wave” of AI is now bringing them together. This book, Neuro-Symbolic Artificial Intelligence: The State of the Art, provides an overview of this development in AI. The two approaches differ significantly in terms of their strengths and weaknesses and, from a cognitive-science perspective, there is a question as to how a neural system can perform symbol manipulation, and how the representational differences between these two approaches can be bridged. The book presents 17 overview papers, all by authors who have made significant contributions in the past few years and starting with a historic overview first seen in 2016. With just seven months elapsed from invitation to authors to final copy, the book is as up-to-date as a published overview of this subject can be. Based on the editors’ own desire to understand the current state of the art, this book reflects the breadth and depth of the latest developments in neuro-symbolic AI, and will be of interest to students, researchers, and all those working in the field of Artificial Intelligence.

The theory and practice of AI and ML in marketing saving time, money

Decode AI algorithms with precision using this comprehensive MCQ mastery guide on artificial intelligence. Tailored for students, developers, and AI enthusiasts, this resource offers a curated selection of practice questions covering key concepts, techniques, and applications in AI. Delve deep into machine learning, neural networks, and natural language processing while enhancing your problem-solving skills. Whether you're preparing for exams or seeking to reinforce your practical knowledge, this guide equips you with the tools needed to excel. Master artificial intelligence and unlock the potential of intelligent systems with confidence using this indispensable resource.

This accessible and engaging textbook presents a concise introduction to the exciting field of artificial intelligence (AI). The broad-ranging discussion covers the key subdisciplines within the field, describing practical algorithms and concrete applications in the areas of agents, logic, search, reasoning under uncertainty, machine learning, neural networks, and reinforcement learning. Fully revised and updated, this much-anticipated second edition also includes new material on deep learning. Topics and features: presents an application-focused and hands-on approach to learning, with supplementary teaching resources provided at an associated website; contains numerous study exercises and solutions, highlighted examples, definitions, theorems, and illustrative cartoons; includes chapters on predicate logic, PROLOG, heuristic search, probabilistic reasoning, machine learning and data mining, neural networks and reinforcement learning; reports on developments in deep learning, including applications of neural networks to generate creative content such as text, music and art (NEW); examines performance evaluation of clustering algorithms, and presents two practical examples explaining Bayes’ theorem and its relevance in everyday life (NEW); discusses search algorithms, analyzing the cycle check, explaining route planning for car navigation systems, and introducing Monte Carlo Tree Search (NEW); includes a section in the introduction on AI and society, discussing the implications of AI on topics such as employment and transportation (NEW). Ideal for foundation courses or modules on AI, this easy-to-read textbook offers an excellent overview of the field for students of computer science and other technical disciplines, requiring no more than a high-school level of knowledge of mathematics to understand the material.

This book constitutes the thoroughly refered post-proceedings of the 11th Conference of the Spanish Association for Artificial Intelligence, CAEPIA 2005, held in Santiago de Compostela, Spain in November 2005. The 48 revised full papers presented together with an invited paper were carefully selected. The papers span the entire spectrum of artificial intelligence from foundational and theoretical issues to advanced applications in various fields.