The BLue Amazon Brain (BLAB): A Modular Architecture of Services about the Brazilian Maritime Territory
This work addresses the problem of scattered domain information and lack of training data for AI in technical domains like environmental monitoring, but it is incremental as it builds on existing NLP modules and architectures.
The paper tackles the challenge of developing an artificial agent for the Brazilian maritime territory (Blue Amazon) by creating a modular architecture called BLAB, which integrates services like a conversational facility (BLAB-Chat) and a news reporter to disseminate information and raise environmental awareness, though no concrete performance numbers are provided.
We describe the first steps in the development of an artificial agent focused on the Brazilian maritime territory, a large region within the South Atlantic also known as the Blue Amazon. The "BLue Amazon Brain" (BLAB) integrates a number of services aimed at disseminating information about this region and its importance, functioning as a tool for environmental awareness. The main service provided by BLAB is a conversational facility that deals with complex questions about the Blue Amazon, called BLAB-Chat; its central component is a controller that manages several task-oriented natural language processing modules (e.g., question answering and summarizer systems). These modules have access to an internal data lake as well as to third-party databases. A news reporter (BLAB-Reporter) and a purposely-developed wiki (BLAB-Wiki) are also part of the BLAB service architecture. In this paper, we describe our current version of BLAB's architecture (interface, backend, web services, NLP modules, and resources) and comment on the challenges we have faced so far, such as the lack of training data and the scattered state of domain information. Solving these issues presents a considerable challenge in the development of artificial intelligence for technical domains.