Rapid Development of Compositional AI

• URL: http://arxiv.org/abs/2302.05941v1
• Date: Sun, 12 Feb 2023 15:41:14 GMT
• Title: Rapid Development of Compositional AI
• Authors: Lee Martie, Jessie Rosenberg, Veronique Demers, Gaoyuan Zhang, Onkar Bhardwaj, John Henning, Aditya Prasad, Matt Stallone, Ja Young Lee, Lucy Yip, Damilola Adesina, Elahe Paikari, Oscar Resendiz, Sarah Shaw, David Cox
• Abstract summary: (Bee)* is a framework for building integrated, scalable, and interactive compositional AI applications. We show how (Bee)* supports building integrated, scalable, and interactive compositional AI applications with a simplified developer experience.
• Score: 5.1158486685898374
• License: http://creativecommons.org/licenses/by/4.0/
• 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.

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