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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.
List of 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 Challenge for Autonomous Vehicles. Chapter 6 Forms of Machine Learning. Chapter 7 Types of Machine-Learning 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¿TöSequence Learning. Chapter 14 Attention Is All You Need. Chapter 15 Large Language Models and Multimodal Systems. Chapter 16 End¿töend Neural Networks. Chapter 17 A Question of Strategy. Chapter 18 Green Lights Ahead!. Bibliography. Index
About the author
J. Mark Bishop has served as Professor of Cognitive Computing and Director of The Centre for AI and Analytics (TCIDA), at Goldsmiths, University of London. Mark was elected Chair of the AISB (the UK professional body for AI, and the oldest such organisation in the world) from 2010-2014. He currently acts as Chief Scientific Advisor to Fact3602 and is an International Fellow of the Karel ¿apek Center, Praha, Czech Republic.
Gabriel Seiberth is a distinguished automotive industry professional with 25 years of experience in management consulting and technology. He currently holds a top management position at a leading global electronics and services company for the automotive industry. Previously, he served as Managing Director at a leading global technology and consulting firm, where he authored several influential thought leadership pieces around autonomous driving.
