Generative AI is a paradigm shift for defense and intelligence missions. The Microsoft for defense and intelligence team recognizes its potential to automate the fusion and analysis of multiple sources of data using natural language to aid in the process. It facilitates the creation of realistic and diverse scenarios and simulations that can augment human capabilities and inform decision-making. Microsoft Azure OpenAI Service is a powerful tool for processing synthetic satellite imagery and terrain maps, synthesizing speech and text for language translation, analysis, and creating immersive virtual environments for training and testing. It provides a capability that can empower defense and intelligence professionals to achieve mission success with greater speed, accuracy, and efficiency.
The breadth to which Azure OpenAI technologies can be applied is increasing exponentially but must be applied responsibly and in accordance with responsible AI principles and policies.
As a former defense leader, this blog considers the breadth of opportunities and will highlight three use cases covering the broad spectrum of defense and intelligence missions:
These use cases focus on low-classification data, which can be securely optimized by harnessing the collective value and capabilities of Azure OpenAI and the Microsoft Azure Cloud Services.
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Azure OpenAI has created new possibilities that were once seen as very hard and costly to implement in military systems.
For ‘non-tactical’ scenarios, cloud-based computing provides the most secure and highest security offering available. The computing resources can be put to work continually enhancing and optimizing planning, analysis, and operational management using the best tools available. Advances in Azure OpenAI and multi-agent frameworks usher in a new era of the role of humans in the loop as a manager and orchestrator of agent computing resources rather than conducting technical analysis and planning. The result is a substantial increase in the speed and capacity of our valuable skilled resources to achieve the mission.
When we consider ‘tactical’ scenarios, the limitation of bandwidth, weight, and power can influence the adoption of Azure OpenAI applications that can be deployed. Smaller models are less capable and must be finely tuned to their purpose to be highly effective. Additionally, carrying a large number of models not relevant to the mission takes up valuable computing and power resources. As such, when deciding on what Azure OpenAI to access in the field, nations must have robust deployment, collection, and ModelOps pipeline updates that can continually—at speed—update models for specificity and relevance to the tactical edge. The ability to access models in disrupted, disconnected, intermittent, and low-bandwidth (DDIL) environments is essential when operating as close to the edge as Size, Weight, Power, and Compute (SWaP-C) permits.
Microsoft is committed to responsible use of AI. That is why Microsoft has long been a leader in ensuring the development of responsible AI, with principles designed to put people first. We believe AI exists to enhance human capabilities, not replace them, and we are committed to empowering responsible AI practices that benefit the world at large. The six key principles for responsible AI include:
The Microsoft Responsible AI Standard provides actionable guidance for their teams, going beyond high-level principles to create AI systems that uphold these values and earn society’s trust. We also have an Office of Responsible AI that sets governance policies, advises leadership, and ensures responsible practices across the company.
Microsoft Azure OpenAI Service offers unprecedented opportunities to augment human capabilities and enhance decision-making across the defense ecosystem. Harness the value of Azure OpenAI to achieve mission success across the spectrum of capability with greater speed, accuracy, and efficiency.
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Source: Microsoft Industry Blog