The panel on “AI and Autonomous Systems (AI*AS)” is designed to address the latest advances of AI and the cutting-edge challenges to Autonomous Systems (AS) in symbiotic human and robot environment for real-time intelligence generation beyond learning. It aims to enrich the coverage of IEEE SMC’23 program and to enable audience, particularly young researchers, to interact with leading scientists and experts in our fields. Participants may be enlightened by the panelists’ vision and thought to emerging AI technologies and their Intelligence Science (IS) foundations towards autonomous systems. Brain-inspired systems (BIS) and training-free Autonomous AI (AAI) will be explored, underpinned by IS foundations and contemporary Intelligent Mathematics (IM). This spectrum of basic research will enable the next-generation of Cognitive Computers (kC) powered by non-pretrained and non-preprogramed methodologies towards the ultimate aim of autonomous real-time intelligence generation.

The theme of the AI*AS panel is on the challenges and constraints of training-based AI towards autonomous systems. A recent discovery in intelligence science reveals that abstract intelligence sharable by humans and machines is not simply aggregated from data, information, and knowledge. Instead, it is generated by inductive reasoning. Therefore, a fundamental question is that if AS’ represented by the brain is merely training-based and language driven? How real-time intelligence generation may be implemented beyond classical pretrained (neural networks) and preprogrammed (von Neumann computers)? Therefore, SMC theories play an irreplaceable role for synergizing symbiotic human-machine systems as a generic platform powered by IS and IM. This leads to the contemporary brain-centered Natural Intelligence (NI) embodied by AAI for revealing the fundamental constraints of and potential theoretical approaches to classical training-based AI.

Interactive discussions between the panelists and audience will provide a unique opportunity for young scientists to learn from the outstanding scholars and multidisciplinary experts.