AI Enabling Technologies: A Survey

TL;DR

This survey reviews the diverse enabling technologies for end-to-end AI systems, emphasizing their roles in defense and intelligence applications, and highlights recent advances across academia, industry, and government.

Contribution

It provides a comprehensive overview of AI components, terminology, and recent technological developments relevant to defense and intelligence sectors.

Findings

AI systems integrate multiple technological components.

Recent advances span academia, industry, and government.

Success depends on the effective integration of diverse AI technologies.

Abstract

Artificial Intelligence (AI) has the opportunity to revolutionize the way the United States Department of Defense (DoD) and Intelligence Community (IC) address the challenges of evolving threats, data deluge, and rapid courses of action. Developing an end-to-end artificial intelligence system involves parallel development of different pieces that must work together in order to provide capabilities that can be used by decision makers, warfighters and analysts. These pieces include data collection, data conditioning, algorithms, computing, robust artificial intelligence, and human-machine teaming. While much of the popular press today surrounds advances in algorithms and computing, most modern AI systems leverage advances across numerous different fields. Further, while certain components may not be as visible to end-users as others, our experience has shown that each of these interrelated components play a major role in the success or failure of an AI system. This article is meant to highlight many of these technologies that are involved in an end-to-end AI system. The goal of this article is to provide readers with an overview of terminology, technical details and recent highlights from academia, industry and government. Where possible, we indicate relevant resources that can be used for further reading and understanding.