TY - GEN
T1 - Empowering Generative AI with Knowledge Base 4.0
T2 - 2023 IEEE International Conference on Web Services, ICWS 2023
AU - Beheshti, Amin
PY - 2023
Y1 - 2023
N2 - Intelligence refers to the ability to acquire and apply knowledge and skills, which comprises three fundamental components, namely knowledge, experience, and creativity. Consequently, there exist three primary Artificial Intelligence (AI) systems, namely Analytical AI, Cognitive AI, and Generative AI. Analytical AI is primarily concerned with comprehending the data and transforming it into contextualized data and knowledge. On the other hand, Cognitive AI is centered on understanding experience and aims to annotate, enrich, and utilize the knowledge, to facilitate decision-making. Lastly, Generative AI delves into the neural mechanisms involved in creative thinking and problem-solving, with a focus on enhancing the process of acquiring and applying knowledge and skills. This paper presents Knowledge Base 4.0 as the backend data for AI engines, which allows for linking knowledge and experience to enable empowering generative AI. The objective is not only to facilitate generating new content (such as text and images) but also to generate new processes when/if needed. We present the architecture of Knowledge Base 4.0 and the design and development of data services that construct and maintain this robust Knowledge Base. Additionally, we provide use cases in various domains, including health, policing, banking, and education.
AB - Intelligence refers to the ability to acquire and apply knowledge and skills, which comprises three fundamental components, namely knowledge, experience, and creativity. Consequently, there exist three primary Artificial Intelligence (AI) systems, namely Analytical AI, Cognitive AI, and Generative AI. Analytical AI is primarily concerned with comprehending the data and transforming it into contextualized data and knowledge. On the other hand, Cognitive AI is centered on understanding experience and aims to annotate, enrich, and utilize the knowledge, to facilitate decision-making. Lastly, Generative AI delves into the neural mechanisms involved in creative thinking and problem-solving, with a focus on enhancing the process of acquiring and applying knowledge and skills. This paper presents Knowledge Base 4.0 as the backend data for AI engines, which allows for linking knowledge and experience to enable empowering generative AI. The objective is not only to facilitate generating new content (such as text and images) but also to generate new processes when/if needed. We present the architecture of Knowledge Base 4.0 and the design and development of data services that construct and maintain this robust Knowledge Base. Additionally, we provide use cases in various domains, including health, policing, banking, and education.
UR - http://www.scopus.com/inward/record.url?scp=85173859886&partnerID=8YFLogxK
U2 - 10.1109/ICWS60048.2023.00103
DO - 10.1109/ICWS60048.2023.00103
M3 - Conference proceeding contribution
AN - SCOPUS:85173859886
SN - 9798350304862
SP - 763
EP - 771
BT - 2023 IEEE International Conference on Web Services IEEE ICWS 2023
A2 - Ardagna, Claudio
A2 - Benatallah, Boualem
A2 - Bian, Hongyi
A2 - Chang, Carl K.
A2 - Chang, Rong N.
A2 - Fan, Jing
A2 - Fox, Geoffrey C.
A2 - Jin, Zhi
A2 - Liu, Xuanzhe
A2 - Ludwig, Heiko
A2 - Sheng, Michael
A2 - Yang, Jian
PB - Institute of Electrical and Electronics Engineers (IEEE)
CY - Piscataway, NJ
Y2 - 2 July 2023 through 8 July 2023
ER -