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Full Description
Driving Intelligence takes a critical and captivating tour of autonomous driving, a phenomenon at the intersection of data-driven platforms, artificial (general) intelligence and the mind. The journey extends from Europe to key areas such as Japan, China, and the US, recognizing the global impact of AI & autonomous driving on high-tech and automotive sectors.
The significance of 'Driving Intelligence' resonates beyond specialized circles, encompassing a spectrum of perspectives - historical, economic, scientific, and philosophical. The book addresses the pressing question of success probabilities and socioeconomic impacts, not just for specialists but for a wider audience keen on understanding the evolution of AI and mobility in the 21st century.
Avoiding partial insights into this domain, the book provides a comprehensive and multifaceted overview which will appeal to a diverse audience including business leaders and policymakers in the mobility and tech industries, governmental bodies, and the general public globally.
Contents
Foreword. Preface. About the Authors. Chapter 1 Self Driving to the Future. Chapter 2 Computing Machinery & Intelligence. Chapter 3 First Steps in Computer Vision. Chapter 4 The Tortoise and the Hare. Chapter 5 The DARPA Grand Challenges. Chapter 6 Forms of Machine Learning. Chapter 7 Types of ML models. Chapter 8 Second & Third DARPA Challenges. Chapter 9 Theory, Empiricism, and Data. Chapter 10 New Forms of Learning. Chapter 11 New Types of Model. Chapter 12 A Whole New Industry Unfolding. Chapter 13 Recurrent Sequence‑To‑Sequence Learning. Chapter 14 Attention Is All You Need. Chapter 15 LLMs and Multi‑Modal Systems. Chapter 16 End‑to‑end Neural Networks. Chapter 17 A Question of Strategy. Chapter 18 Green Lights Ahead!. Bibliography. Index
