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4 May 2018 The AI stack: a blueprint for developing and deploying artificial intelligence
Andrew W. Moore, Martial Hebert, Shane Shaneman
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This paper provides an abstract technology model called the AI Stack for the development and deployment of Artificial Intelligence, and the strategic investment in research, technology, and organizational resources required to achieve asymmetric capability. Over the past five years, there has been a drastic acceleration in the development of artificial intelligence fueled by exponential increases in computational power and machine learning. This has resulted in corporations, institutions, and nation-states vastly accelerating their investment in AI to (a) perceive and synthesize massive amounts of data, (b) understand the contextual importance of the data and potential tactical/strategic impacts, (c) accelerate and optimize decision-making, and (d) enable human augmentation and deploy autonomous systems. From a national security and defense perspective, AI is a crucial technology to enhance situational awareness and accelerate the realization of timely and actionable intelligence that can save lives. For many current defense applications, this often requires the processing of visual data, images, or full motion video from legacy platforms and sensors designed decades before recent advances in machine learning, computer vision, and AI. The AI Stack - and the fusion of the interdependent technology layers contained within it - provides a streamlined approach to visualize, plan, and prioritize strategic investments in commercial technologies and transformational research to leverage and continuously advance AI across operational domains, and achieve asymmetric capability through human augmentation and autonomous systems. One application of AI for the Department of Defense is to provide automation and human augmentation for analyzing full motion video to drastically enhance the safety of our deployed soldiers by enhancing their situational awareness and enabling them to make faster decisions on more timely information to save lives.
© (2018) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Andrew W. Moore, Martial Hebert, and Shane Shaneman "The AI stack: a blueprint for developing and deploying artificial intelligence", Proc. SPIE 10635, Ground/Air Multisensor Interoperability, Integration, and Networking for Persistent ISR IX, 106350C (4 May 2018);

Artificial intelligence

Machine learning


Defense and security

Machine vision

Visual process modeling

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