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Author: George F. Luger
Publisher: Springer Nature
ISBN: 3030718735
Category : Computers
Languages : en
Pages : 267
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Book Description
Knowing our World: An Artificial Intelligence Perspective considers the methodologies of science, computation, and artificial intelligence to explore how we humans come to understand and operate in our world. While humankind’s history of articulating ideas and building machines that can replicate the activity of the human brain is impressive, Professor Luger focuses on understanding the skills that enable these goals. Based on insights afforded by the challenges of AI design and program building, Knowing our World proposes a foundation for the science of epistemology. Taking an interdisciplinary perspective, the book demonstrates that AI technology offers many representational structures and reasoning strategies that support clarification of these epistemic foundations. This monograph is organized in three Parts; the first three chapters introduce the reader to the foundations of computing and the philosophical background that supports the AI tradition. These three chapters describe the origins of AI, programming as iterative refinement, and the representations and very high-level language tools that support AI application building. The book’s second Part introduces three of the four paradigms that represent research and development in AI over the past seventy years: the symbol-based, connectionist, and complex adaptive systems. Luger presents several introductory programs in each area and demonstrates their use. The final three chapters present the primary theme of the book: bringing together the rationalist, empiricist, and pragmatist philosophical traditions in the context of a Bayesian world view. Luger describes Bayes' theorem with a simple proof to demonstrate epistemic insights. He describes research in model building and refinement and several philosophical issues that constrain the future growth of AI. The book concludes with his proposal of the epistemic stance of an active, pragmatic, model-revising realism.
Author: George F. Luger
Publisher: Springer
ISBN: 9783030718725
Category : Computers
Languages : en
Pages : 253
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Book Description
Knowing our World: An Artificial Intelligence Perspective considers the methodologies of science, computation, and artificial intelligence to explore how we humans come to understand and operate in our world. While humankind’s history of articulating ideas and building machines that can replicate the activity of the human brain is impressive, Professor Luger focuses on understanding the skills that enable these goals. Based on insights afforded by the challenges of AI design and program building, Knowing our World proposes a foundation for the science of epistemology. Taking an interdisciplinary perspective, the book demonstrates that AI technology offers many representational structures and reasoning strategies that support clarification of these epistemic foundations. This monograph is organized in three Parts; the first three chapters introduce the reader to the foundations of computing and the philosophical background that supports the AI tradition. These three chapters describe the origins of AI, programming as iterative refinement, and the representations and very high-level language tools that support AI application building. The book’s second Part introduces three of the four paradigms that represent research and development in AI over the past seventy years: the symbol-based, connectionist, and complex adaptive systems. Luger presents several introductory programs in each area and demonstrates their use. The final three chapters present the primary theme of the book: bringing together the rationalist, empiricist, and pragmatist philosophical traditions in the context of a Bayesian world view. Luger describes Bayes' theorem with a simple proof to demonstrate epistemic insights. He describes research in model building and refinement and several philosophical issues that constrain the future growth of AI. The book concludes with his proposal of the epistemic stance of an active, pragmatic, model-revising realism.
Author: George F. Luger
Publisher: Springer Nature
ISBN: 3030718735
Category : Computers
Languages : en
Pages : 267
Get Book Here
Book Description
Knowing our World: An Artificial Intelligence Perspective considers the methodologies of science, computation, and artificial intelligence to explore how we humans come to understand and operate in our world. While humankind’s history of articulating ideas and building machines that can replicate the activity of the human brain is impressive, Professor Luger focuses on understanding the skills that enable these goals. Based on insights afforded by the challenges of AI design and program building, Knowing our World proposes a foundation for the science of epistemology. Taking an interdisciplinary perspective, the book demonstrates that AI technology offers many representational structures and reasoning strategies that support clarification of these epistemic foundations. This monograph is organized in three Parts; the first three chapters introduce the reader to the foundations of computing and the philosophical background that supports the AI tradition. These three chapters describe the origins of AI, programming as iterative refinement, and the representations and very high-level language tools that support AI application building. The book’s second Part introduces three of the four paradigms that represent research and development in AI over the past seventy years: the symbol-based, connectionist, and complex adaptive systems. Luger presents several introductory programs in each area and demonstrates their use. The final three chapters present the primary theme of the book: bringing together the rationalist, empiricist, and pragmatist philosophical traditions in the context of a Bayesian world view. Luger describes Bayes' theorem with a simple proof to demonstrate epistemic insights. He describes research in model building and refinement and several philosophical issues that constrain the future growth of AI. The book concludes with his proposal of the epistemic stance of an active, pragmatic, model-revising realism.
Author: Kai-Fu Lee
Publisher: Crown Currency
ISBN: 0593238311
Category : Social Science
Languages : en
Pages : 497
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Book Description
How will AI change our world within twenty years? A pioneering technologist and acclaimed writer team up for a “dazzling” (The New York Times) look at the future that “brims with intriguing insights” (Financial Times). This edition includes a new foreword by Kai-Fu Lee. A BEST BOOK OF THE YEAR: The Wall Street Journal, The Washington Post, Financial Times Long before the advent of ChatGPT, Kai-Fu Lee and Chen Qiufan understood the enormous potential of artificial intelligence to transform our daily lives. But even as the world wakes up to the power of AI, many of us still fail to grasp the big picture. Chatbots and large language models are only the beginning. In this “inspired collaboration” (The Wall Street Journal), Lee and Chen join forces to imagine our world in 2041 and how it will be shaped by AI. In ten gripping, globe-spanning short stories and accompanying commentary, their book introduces readers to an array of eye-opening settings and characters grappling with the new abundance and potential harms of AI technologies like deep learning, mixed reality, robotics, artificial general intelligence, and autonomous weapons.
Author: Amir Husain
Publisher: Simon and Schuster
ISBN: 1501144677
Category : Computers
Languages : en
Pages : 224
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Book Description
Explores universal questions about humanity's capacity for living and thriving in the coming age of sentient machines and AI, examining debates from opposing perspectives while discussing emerging intellectual diversity and its potential role in enabling a positive life.
Author: Zaremohzzabieh, Zeinab
Publisher: IGI Global
ISBN:
Category : Computers
Languages : en
Pages : 519
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Book Description
In an era defined by the relentless march of technology, the seamless integration of Artificial Intelligence (AI) into our daily lives has ushered in a transformative landscape. At the forefront of this evolution are the Digital Natives of Generation AI, navigating the complexities of a digital world where algorithms are integral to their daily experiences. This juncture presents a dual influence, marked by the continuous progression of technological advancements and the dynamic ways the youngest members of our society engage with and adapt to the digital environment. As we stand at the crossroads of youth studies and AI, there arises a pressing need to comprehend the profound impact of this convergence on the future leaders of our world. Addressing this imperative, Exploring Youth Studies in the Age of AI emerges as a comprehensive solution to unravel the complexities and opportunities within this evolving landscape. This book, meticulously crafted for academics, researchers, educators, policymakers, and technology ethicists, serves as a guiding beacon in understanding how AI shapes the experiences of today's youth and, in turn, how youth culture influences the development and application of AI technologies. With a collection of enlightening chapters covering topics from "Data-Driven Pedagogies" to "Ethical AI: Guiding Principles for Youth-Centric Development," the book delves deep into the diverse dimensions of this intersection, providing actionable insights and fostering a nuanced understanding for those invested in the ethical, social, and educational implications of AI within the context of youth.
Author: Mehta, Shilpa
Publisher: IGI Global
ISBN:
Category : Computers
Languages : en
Pages : 434
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Book Description
In the digital landscape, the Metaverse emerges as a frontier of boundless possibilities. Yet, its potential remains largely untapped. The pressing challenge lies in harnessing the power of machine learning to navigate this uncharted territory, where virtual reality, augmented reality, and immersive technologies converge to redefine human interaction and experience. Impact and Potential of Machine Learning in the Metaverse offers a comprehensive examination of how machine learning techniques can shape the future of the Metaverse. This advanced work addresses key domains such as healthcare, education, gaming, and beyond. By delving into topics like digital twins in healthcare and blockchain-enabled security, the book not only sheds light on advancements but also confronts challenges head-on, inspiring scholars to explore new research directions and interdisciplinary collaborations. Through real-world case studies and practical applications, readers gain actionable insights into leveraging machine learning for transformative impact in the Metaverse.
Author: Rishabha Malviya
Publisher: CRC Press
ISBN: 1000638901
Category : Computers
Languages : en
Pages : 357
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Book Description
Nowadays, raw biological data can be easily stored as databases in computers but extracting the required information is the real challenge for researchers. For this reason, bioinformatics tools perform a vital role in extracting and analyzing information from databases. Bioinformatics Tools and Big Data Analytics for Patient describes the applications of bioinformatics, data management, and computational techniques in clinical studies and drug discovery for patient care. The book gives details about the recent developments in the fields of artificial intelligence, cloud computing, and data analytics. It highlights the advances in computational techniques used to perform intelligent medical tasks. Features: Presents recent developments in the fields of artificial intelligence, cloud computing, and data analytics for improved patient care. Describes the applications of bioinformatics, data management, and computational techniques in clinical studies and drug discovery. Summarizes several strategies, analyses, and optimization methods for patient healthcare. Focuses on drug discovery and development by cloud computing and data-driven research The targeted audience comprises academics, research scholars, healthcare professionals, hospital managers, pharmaceutical chemists, the biomedical industry, software engineers, and IT professionals.
Author: Yuriy S. Vasiliev
Publisher: Springer Nature
ISBN: 3030988325
Category : Technology & Engineering
Languages : en
Pages : 619
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Book Description
This book covers the results of research that has been obtained during the last decades by scholars representing several scientific schools working in the field of theory of systems and system analysis. In the book chapters, attention is paid to the development of the general theory of systems’ provisions, approaches, models, and methods of system analysis; such as the concepts of an open system and adaptive systems; the concepts of “the movable equilibrium” and “disequilibrium”, the approach of “growing” the system and its developing through innovations; the system-target approach, systems’ regularities; ontological, cognitive and logical-linguistic models of systems, etc. The book includes parts devoted to the general theoretical and philosophical-methodological problems of systems theory; methods and models of system analysis; innovation technologies in technical and socioeconomic systems; system analyses in the educational process, and higher education management. The materials of the book may be of interest to researchers and specialists working in the field of systems analysis, engineering, computer technologies, including human–computer interaction in socio-technical systems; for the representatives of the academic and engineering society.
Author: Brian Cantwell Smith
Publisher: MIT Press
ISBN: 0262355213
Category : Computers
Languages : en
Pages : 179
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Book Description
An argument that—despite dramatic advances in the field—artificial intelligence is nowhere near developing systems that are genuinely intelligent. In this provocative book, Brian Cantwell Smith argues that artificial intelligence is nowhere near developing systems that are genuinely intelligent. Second wave AI, machine learning, even visions of third-wave AI: none will lead to human-level intelligence and judgment, which have been honed over millennia. Recent advances in AI may be of epochal significance, but human intelligence is of a different order than even the most powerful calculative ability enabled by new computational capacities. Smith calls this AI ability “reckoning,” and argues that it does not lead to full human judgment—dispassionate, deliberative thought grounded in ethical commitment and responsible action. Taking judgment as the ultimate goal of intelligence, Smith examines the history of AI from its first-wave origins (“good old-fashioned AI,” or GOFAI) to such celebrated second-wave approaches as machine learning, paying particular attention to recent advances that have led to excitement, anxiety, and debate. He considers each AI technology's underlying assumptions, the conceptions of intelligence targeted at each stage, and the successes achieved so far. Smith unpacks the notion of intelligence itself—what sort humans have, and what sort AI aims at. Smith worries that, impressed by AI's reckoning prowess, we will shift our expectations of human intelligence. What we should do, he argues, is learn to use AI for the reckoning tasks at which it excels while we strengthen our commitment to judgment, ethics, and the world.
Author: Kartik Hosanagar
Publisher: Penguin
ISBN: 0525560904
Category : Business & Economics
Languages : en
Pages : 274
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Book Description
A Wharton professor and tech entrepreneur examines how algorithms and artificial intelligence are starting to run every aspect of our lives, and how we can shape the way they impact us Through the technology embedded in almost every major tech platform and every web-enabled device, algorithms and the artificial intelligence that underlies them make a staggering number of everyday decisions for us, from what products we buy, to where we decide to eat, to how we consume our news, to whom we date, and how we find a job. We've even delegated life-and-death decisions to algorithms--decisions once made by doctors, pilots, and judges. In his new book, Kartik Hosanagar surveys the brave new world of algorithmic decision-making and reveals the potentially dangerous biases they can give rise to as they increasingly run our lives. He makes the compelling case that we need to arm ourselves with a better, deeper, more nuanced understanding of the phenomenon of algorithmic thinking. And he gives us a route in, pointing out that algorithms often think a lot like their creators--that is, like you and me. Hosanagar draws on his experiences designing algorithms professionally--as well as on history, computer science, and psychology--to explore how algorithms work and why they occasionally go rogue, what drives our trust in them, and the many ramifications of algorithmic decision-making. He examines episodes like Microsoft's chatbot Tay, which was designed to converse on social media like a teenage girl, but instead turned sexist and racist; the fatal accidents of self-driving cars; and even our own common, and often frustrating, experiences on services like Netflix and Amazon. A Human's Guide to Machine Intelligence is an entertaining and provocative look at one of the most important developments of our time and a practical user's guide to this first wave of practical artificial intelligence.
