Scalability is a critical concept in many engineering disciplines and is crucial to realizing operational AI capabilities. We identify three areas of focus to advance scalable AI:
• Scalable management of data and models to overcome data scarcity and collection challenges, and promote reusing and recombining capabilities to scale across missions
• Enterprise scalability of AI development and deployment including establishing production pipelines, extensible system architectures, and modern policies and acquisition practices to maintain advanced capabilities and take advantage of rapid innovation in AI technologies
• Scalable algorithms and infrastructure to fully apply the power of AI to critical missions, including centralized data center capabilities and distributed cloud-enabled and network-enabled applications for edge devices
For each area, we identify ongoing work as well as challenges and opportunities in developing and deploying AI systems at scale.
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