Roles of Artificial Intelligence and Machine Learning in Future Mobility

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Roles of Artificial Intelligence and Machine Learning in Future Mobility Huang Guangbin Professor of School of Electrical and Electronic Engineering Nanyang Technological University, Singapore ITU/IMDA Workshop on How Communications will Change Vehicles and Transport July 6 2017

Three Historical Revolutions I Still in the bottom of the brewing period of the "intelligence era, the eve of the big outbreak of "intelligence era" Agricultural Revolution Industrial Revolution Intelligent Revolution Tens of Thousands years ago Hundreds years ago Several years ago (Since 2010) Time 2

Rethink Artificial Intelligence and Machine Learning Machine Learning Artificial Intelligence Earliest Deep Learning (1960s) AI Winter (1970s) Neural Networks reviving Almost all Deep Learning (CNN, BP, etc) techniques proposed in 1980s Neucognition (1979) ELMs direct biological evidence found in 2012 Extreme Learning Machines (ELMs) born in 2004 Deep Learning reviving in 2004 due to high performance of computing 1950s 1970s 1980s 2010 Present Time 3

Intelligent Vehicles

AI / ML and Automation of Vehicles Advance of Artificial Intelligence and Machine Learning 5

AI / ML Making Vehicles Become Moving Data Centers and Intelligent Things 6

Pervasive Intelligence Everywhere in Vehicles 7

Intelligent Transportation Systems

Intelligence Transportation System 9

Intelligence Transportation System 10

Intelligence Scheduling and Planning 11

Intelligence Parking System 12

Autonomous Systems

Advanced Driver Assistance System (ADAS) 14

Fully Autonomous Driving 15

Future Mobility and New Economy Model

Opporunities: Internet of Intelligent Things in Future Mobility Things ELMs and other AI techniques (FPGA, ASIC, Accelarators, Memristors, Neuromorphic) Intelligent Things (eg. Intelligent engine, intelligent devices, intelligent sensors, intelligent cameras, etc) 17

Opportunities: Niche Technologies for Future Mobility Smart Materials Machine Learning Smart Sensors Artificial Intelligence 18

Opportunities: Cloud Intelligence and Local Intelligence in Future Mobility Deep Learning (and other heavy learning mainly in cloud and servers) Universal Learning(for both Cloud Learning and Local Learning) ELM (and other light learning in sensors and local devices) 19

Effects of AI / ML and Autonomous Driving Thousands of positive values / reasons New economy without or with less human participation Critical worries / contradictions: E / The dominance of human and biological intelligence will be challenged by the intelligence created by human. According to Darwin's theory of evolution, with the popularity and deepening of intelligence, some capabilities of human will be degraded (e.g, human s driving capability weakening in autonomous driving era). Although machine intelligence can be created by mankind, it is likely to become uncontrollable and uncertain. Positive / negative intelligence? L Agriculture revolution Industrial Revolution Intelligence Revolution Turning Point 1 Turning Point 2 Non-living Intelligence 20