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Feds at the EdgeAuthor: FedInsider
The federal government is changing the way it handles data. It is transitioning from an on premises data center approach to the cloud. Further, it is getting data from a wide ranging number of sensors. Feds at the Edge is a podcast that addresses those concerns Language: en Genres: Government, Technology Contact email: Get it Feed URL: Get it iTunes ID: Get it |
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243 Operationalizing Private AI for Federal Missions
Wednesday, 8 April, 2026
= = = = 46:18 We have all seen the power of AI; the question we have is, can it be implemented in a secure federal environment? Today, we sat down with three experts who have successfully applied powerful private AI tools to the federal government. The panel emphasized the need for responsible implementation, the transformational impact of AI, and the roles required to support AI initiatives in government. Responible. Natalie Bud Smitth from the Library of Congress argues that the key to using data safely is to carefully examine end objectives and the workflow for that experience. When done correctly, data repositories are curated, which enables proper compliance with federal standards. This approach has proven to be truly transformational. The federal government had given the Idaho National Lab aggressive timelines to deploy AI. His primary limitation is that nuclear data may be excluded from large, or frontier, AI models like ChatGPT. As a result, he has managed to capture data owned by the INL and fine-tune it into a dataset usable by private AI models. Using this model, he has been shocked by its transformative power. Experience is another key factor to consider. It is obvious that nobody has 10 years of experience with today's AI models. Brenden Wright shared his experience in building an AI lab at Keysight, stressing the importance of experimentation and collaboration. When ideas are reviewed by others in the same predicament, federal leaders can deploy AI to emphasize privacy and security.
