3 Papers

AIApr 6, 2023
The Governance of Physical Artificial Intelligence

Yingbo Li, Anamaria-Beatrice Spulber, Yucong Duan

Physical artificial intelligence can prove to be one of the most important challenges of the artificial intelligence. The governance of physical artificial intelligence would define its responsible intelligent application in the society.

AIMay 13, 2021
Physical Artificial Intelligence: The Concept Expansion of Next-Generation Artificial Intelligence

Yingbo Li, Yucong Duan, Anamaria-Beatrice Spulber et al.

Artificial Intelligence has been a growth catalyst to our society and is cosidered across all idustries as a fundamental technology. However, its development has been limited to the signal processing domain that relies on the generated and collected data from other sensors. In recent research, concepts of Digital Artificial Intelligence and Physicial Artifical Intelligence have emerged and this can be considered a big step in the theoretical development of Artifical Intelligence. In this paper we explore the concept of Physicial Artifical Intelligence and propose two subdomains: Integrated Physicial Artifical Intelligence and Distributed Physicial Artifical Intelligence. The paper will also examine the trend and governance of Physicial Artifical Intelligence.

AIMay 9, 2021
Swarm Differential Privacy for Purpose Driven Data-Information-Knowledge-Wisdom Architecture

Yingbo Li, Yucong Duan, Zakaria Maama et al.

Privacy protection has recently been in the spotlight of attention to both academia and industry. Society protects individual data privacy through complex legal frameworks. The increasing number of applications of data science and artificial intelligence has resulted in a higher demand for the ubiquitous application of the data. The privacy protection of the broad Data-Information-Knowledge-Wisdom (DIKW) landscape, the next generation of information organization, has taken a secondary role. In this paper, we will explore DIKW architecture through the applications of the popular swarm intelligence and differential privacy. As differential privacy proved to be an effective data privacy approach, we will look at it from a DIKW domain perspective. Swarm Intelligence can effectively optimize and reduce the number of items in DIKW used in differential privacy, thus accelerating both the effectiveness and the efficiency of differential privacy for crossing multiple modals of conceptual DIKW. The proposed approach is demonstrated through the application of personalized data that is based on the open-sourse IRIS dataset. This experiment demonstrates the efficiency of Swarm Intelligence in reducing computing complexity.