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Rapid Development of Compositional AI

Authors :
Martie, Lee
Rosenberg, Jessie
Demers, Veronique
Zhang, Gaoyuan
Bhardwaj, Onkar
Henning, John
Prasad, Aditya
Stallone, Matt
Lee, Ja Young
Yip, Lucy
Adesina, Damilola
Paikari, Elahe
Resendiz, Oscar
Shaw, Sarah
Cox, David
Source :
2023 IEEE/ACM 45th International Conference on Software Engineering: New Ideas and Emerging Technologies Results Track (ICSE-NIER), Melbourne, Australia, 2023, pp. (forthcoming)
Publication Year :
2023

Abstract

Compositional AI systems, which combine multiple artificial intelligence components together with other application components to solve a larger problem, have no known pattern of development and are often approached in a bespoke and ad hoc style. This makes development slower and harder to reuse for future applications. To support the full rapid development cycle of compositional AI applications, we have developed a novel framework called (Bee)* (written as a regular expression and pronounced as "beestar"). We illustrate how (Bee)* supports building integrated, scalable, and interactive compositional AI applications with a simplified developer experience.<br />Comment: Accepted to ICSE 2023, NIER track

Details

Database :
arXiv
Journal :
2023 IEEE/ACM 45th International Conference on Software Engineering: New Ideas and Emerging Technologies Results Track (ICSE-NIER), Melbourne, Australia, 2023, pp. (forthcoming)
Publication Type :
Report
Accession number :
edsarx.2302.05941
Document Type :
Working Paper