Authors Omar Santos and Petar Radanliev offer a comprehensive exploration of artificial intelligence (AI) and machine learning (ML), from historical contexts to contemporary challenges and future trends. The book’s language is suitable for readers of all backgrounds.

Chapter 1 begins with a historical overview, tracing AI’s evolution and its transformative impact. It introduces Eva, a narrative thread woven throughout to illustrate key concepts. Chapter 2 dives into fundamental AI and ML technologies, discussing leading algorithms and real-world applications. Case studies and ethical reflections punctuate discussions on societal implications in chapter 3, focusing on generative AI and large language models (LLMs) like Hugging Face. Security takes center stage in chapter 4, addressing threats like adversarial attacks and proposing defensive measures. Chapter 5 delves into AI system vulnerabilities and hacking tactics, using examples like MITRE ATLAS to illustrate vulnerabilities and mitigation strategies. Chapter 6 explores system and infrastructure security, emphasizing secure design principles and incident response strategies. Privacy and ethics in an AI-dominated world are scrutinized in chapter 7, discussing data protection, differential privacy, and fairness in AI systems. Chapter 8 looks at legal and regulatory compliance, covering global standards, liability, and the future of AI governance.

Each chapter includes “Test Your Skills” exercises to reinforce learning.

Overall, this book provides a well-rounded education on AI and ML, blending theoretical insights with practical applications and ethical considerations, ensuring relevance in today’s rapidly evolving technological landscape. For readers curious about AI and security, I would suggest two other books also by Omar Santos (and coauthors): The AI revolution in networking, cybersecurity, and emerging technologies [1] and Developing cybersecurity programs and policies in an AI-driven world [2].

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