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Nguyen D: Generative AI for
Cybersecurity

Generative AI for Cybersecurity

Fundamentals, Applications, Risks, and Opportunities

PART I Fundamental Background 1. Generative AI and Its Related Components 2. Cybersecurity Fundamental: Threats, Impacts, and Countermeasures 3. Generative AI as Potential Solutions and Risks to Cybersecurity PART II Applications of Generative AI for Cybersecurity 4. Representation Learning-based Generative AI in Cybersecurity 5. Generative AI for Data Synthesis in Cybersecurity 6. Generative AI for Sequence Learning in Cybersecurity 7. Generative AI for Adversarial Learning in Cybersecurity 8. Case Studies and Detailed Implementation/Experiments PART III Conclusion and Future Perspectives 9. Emerging Topics of Generative AI in Cybersecurity 10. Future Directions and Open Challenges

Depending on who you ask, artificial intelligence is our salvation or our doom; an overhyped, bigoted artist or the ticket to immortality and utopian abundance; just another tech fad or the last invention we need ever make. The AI discourse is confusing, messy, and frustrating. But the technology — and our response to it — will shape the future, whether or not we’re part of the conversation.
Obsolete is&nbsp;for those who are interested in learning more about AI, but unsure of where to start and who to believe. They may feel intimidated by the technical jargon, put off by dry and abstract prose, or skeptical of the loudest voices on the issue (like Elon Musk and Sam Altman). Obsolete will introduce readers to the basics of AI, the idea that it could lead to human extinction, the roiling three-sided debate surrounding extinction fears, and the people and companies trying to build artificial general intelligence (AGI) — that which can outwit humans across the board. The book will grapple with the core arguments animating the AI debates, which are, by turns, uncritically parroted and unduly dismissed. It will also cut through industry hype while seriously entertaining the implications of AGI.
The risk that AGI could result in our extinction is being recognized by a significant and growing number of leading AI researchers, industrialists, and policymakers, along with the wider public. Existential risk from AI has been explored in other books, but Obsolete will be the first to center its analysis on how both capitalist and great power competition make AI more dangerous.
Obsolete will also tackle questions like: Can machines actually outsmart humanity? If so, when could that happen? If AGI is possible, is it inevitable? Why are people trying to build a technology they claim could end the world? Is the idea of AI-driven extinction the product of a big tech conspiracy aiming to hype the technology and control its regulation? Why has the left mostly ignored or dismissed existential risk from AI? Why do some powerful techies welcome human extinction? How could AI enable stable authoritarian regimes? How could killer robots reshape war and the balance of power? What do China and the US want from AI? And why has it become the front line of their brewing Cold War? And finally: What can and should the left do about it?

Power, Profit, And The Race For Machine Superintelligence

Obsolete

How to Make Sense of a Complex Future

The AI Paradox

Medical and Technical Analysis and Signal Processing Perspectives

Exploring Infant Cry

Medical Robots and Devices: New Developments and Advances

AI and Data Science in Precision Medicine, Predictive Analytics, and Medical Practice explores the transformative role of AI and data science in enhancing precision medicine, predictive analytics, and medical practice. The book covers diverse topics such as AI-driven personalized medicine, seizure prediction through EEG analysis, and the application of chaos theory in AI-driven healthcare. The volume also delves into medical practice and education, including ethical considerations, AI-driven supply chain management, and clinical documentation using natural language processing. Furthermore, it examines AI's role in telemedicine, patient engagement, and adherence, offering innovative solutions to improve healthcare delivery and outcomes.

AI and Data Science in Precision Medicine, Predictive Analytics, and Medical Practice

This book frames "theories" as tools for understanding and applying real-world phenomena, bridging classic scholarship with the unprecedented challenges and opportunities posed by machine intelligence, digital platforms, and shifting cultural dynamics. Structured in four sections—Foundational Media Theories, Interaction and Impact Theories, Critical Media Perspective Theories, and Advanced and Future-Facing Theories—the textbook progresses from essential theories like Marshall McLuhan’s&nbsp;and Neil Postman's Media Ecology Theory to cutting-edge concepts like Ambient Media and Attention Economy Theories. With chapters addressing topics such as algorithmic influence, media ecology, participatory media, and posthuman digital embodiment, the book offers a holistic view of media’s past, present, and evolving futures. The 12 future-focused media theories presented include the introduction of Quantum Media Theory and Gestalt Media Theory as an integrated, cross-disciplinary, approach to understanding media theory from a wholistic “whole is more than the sum of its parts” perspective.Jack Myers&nbsp;is a Senior Lecturer on New Media Theory at the University of Arizona School of Information Sciences, author of&nbsp;The Myers Report&nbsp;column at Substack, and&nbsp;founder of the MediaVillage Education Foundation. He was an adjunct professor of Media Business at NYU Steinhardt. His honors include the Excellence in Education Award from the Global Forum on Education &amp; Learning, the George Foster Peabody Award, Academy and EMMY Award nominations for documentary filmmaking, the Crystal Heart Award from the Heartland Film Festival, the World Music Award as its producer, and a Top 10 Most Admired Leader in Tech by Pinnacle Tech Insights.

This book frames "theories" as tools for understanding and applying real-world phenomena, bridging classic scholarship with the unprecedented challenges and opportunities posed by machine intelligence, digital platforms, and shifting cultural dynamics. Structured in four sections—Foundational Media Theories, Interaction and Impact Theories, Critical Media Perspective Theories, and Advanced and Future-Facing Theories—the textbook progresses from essential theories like Marshall McLuhan’s&nbsp;and Neil Postman's Media Ecology Theory to cutting-edge concepts like Ambient Media and Attention Economy Theories. With chapters addressing topics such as algorithmic influence, media ecology, participatory media, and posthuman digital embodiment, the book offers a holistic view of media’s past, present, and evolving futures. The 12 future-focused media theories presented include the introduction of Quantum Media Theory and Gestalt Media Theory as an integrated, cross-disciplinary, approach to understanding media theory from a wholistic “whole is more than the sum of its parts” perspective.

Theories of Culture, Communications, and Consciousness

Media Ecology for the 21st Century

AI Futures

Redefining Arms Races and Contemporary Warfare

Artificial Intelligence and International Security

An expert compilation of on-device training techniques, regulatory frameworks, and ethical considerations of TinyML design and development In Tiny Machine Learning: Design Principles and Applications, a team of distinguished researchers delivers a comprehensive discussion of the critical concepts, design principles, applications, and relevant issues in Tiny Machine Learning (TinyML). Expert contributors introduce a new low power resource, offering vast applications in IoT devices with system-algorithm co-design. Tiny Machine Learning explores TinyML paradigms and enablers, TinyML for anomaly detection, and the learning panorama under TinyML. Readers will find explanations of TinyML devices and tools, power consumption and memory in IoT microcontrollers, and lightweight frameworks for TinyML. The book also describes TinyML techniques for real-time and environmental applications. Additional topics covered in the book include: <ul> <li>A thorough introduction to security and privacy techniques for TinyML devices, including the implementation of novel security schemes</li> <li>Incisive explorations of power consumption and memory in IoT MCUs, including ultralow-power smart IoT devices with embedded TinyML</li> <li>Practical discussions of TinyML research targeting microcontrollers for data extraction and synthesis</li> </ul> Perfect for industry and academic researchers, scientists, and engineers, Tiny Machine Learning will also benefit lecturers and graduate students interested in machine learning.

Tiny Machine Learning: Design Principles and Applications

Advances in Industrial and Systems Engineering

Advances in Human-AI Collaboration

Resistance in the Age of Artificial Intelligence

Algorithmic Capital

Augmented and Virtual Reality in Healthcare

Embedded System and GUI Development using MATLAB for Engineering Applications

Advances in Sustainable Microgrid Technologies

A Microgrid Cluster Management and Internet-of-Things Framework: Fundamentals, Protocols, and Case Studies presents a cutting-edge guide on leveraging IoT technologies to optimize renewable energy integration through microgrid clusters. The book begins by detailing the fundamental aspects of microgrid clusters, encompassing design, control, and optimization. This comprehensive grounding prepares readers for the exploration of IoT integration to harness big data analytics for energy efficiency, power management, fault monitoring, and cybersecurity. The book further delves into the meticulous analysis of protocol selection for effective operation and control. It covers wired protocols such as Modbus, Profibus, and Ethernet, wireless protocols like Zigbee, Wi-Fi, and Bluetooth, and IoT protocols including CoAP, MQTT, and HTTP. By outlining an adaptable framework for interdisciplinary opportunities, this book guides researchers and engineers in creating the flexible, renewable grid of the future.

Fundamentals, Protocols, and Case Studies

A Microgrid Cluster Management and Internet-of-Things Framework

Generative AI for Cybersecurity

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