Rapid Development of Compositional AI
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

TL;DR
This paper introduces (Bee)*, a novel framework designed to streamline the rapid development of compositional AI systems by providing a scalable, integrated, and user-friendly approach.
Contribution
The paper presents (Bee)*, a new framework that standardizes and accelerates the development process of compositional AI applications.
Findings
(Bee)* simplifies the development process.
It enables scalable and interactive AI system construction.
The framework improves reusability and development speed.
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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Taxonomy
TopicsGeochemistry and Geologic Mapping · Explainable Artificial Intelligence (XAI) · Artificial Intelligence in Healthcare and Education
MethodsHigh-Order Consensuses
