Artificial Intelligence Technologies

Artificial intelligence is transforming how people work, communicate, design, analyze data, and solve complex problems. Artificial Intelligence Technologies: Foundations, Systems and Practice provides a clear, practical introduction to the concepts, systems, and tools shaping this rapidly evolving field.

Designed as a one-semester survey, this book guides readers from the foundations and history of AI through machine learning, deep learning, neural networks, natural language processing, large language models, computer vision, multimodal AI, intelligent agents, deployment, and responsible governance. Technical concepts are explained through structured examples, diagrams, analytical frameworks, and practical exercises.

Readers will learn how AI systems perceive environments, learn from data, generate content, use external tools, and operate as autonomous or semi-autonomous agents. The book also examines important real-world concerns, including hallucination, model evaluation, deployment costs, bias, safety, regulation, and ethical responsibility.

Each chapter includes learning objectives, key terminology, summaries, conceptual questions, analytical problems, practical activities, and discussion prompts. Three extensive appendices provide guidance on AI careers, companies, policy organizations, development frameworks, datasets, benchmarks, professional communities, and current learning resources.

Ideal for college students, engineering and technology learners, educators, professionals, and independent learners, this book emphasizes durable understanding rather than short-lived product rankings or model specifications. It equips readers to critically evaluate AI technologies and understand not only what they can do, but how they work, where they fail, and how they should be used responsibly.