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Applying Large Language Models to DoD Software Acquisition: An Initial Experiment.

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posted on 2024-04-03, 23:35 authored by Douglas SchmidtDouglas Schmidt, John RobertJohn Robert

There is considerable interest in using generative AI tools, such as large language models (LLMs), to revolutionize industries and create new opportunities in the commercial and government domains. For many Department of Defense (DoD) software acquisition professionals, the promise of LLMs is appealing, but there’s also a deep-seated concern that LLMs do not address today’s challenges due to privacy concerns, potential for inaccuracy in the output, and lack of confidence or uncertainty about how to use LLMs effectively and responsibly. This blog post is the second in a series dedicated to exploring how generative AI, particularly LLMs such as ChatGPT, Claude, and Gemini, can be applied within the DoD to enhance software acquisition activities.


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This material is based upon work funded and supported by the Department of Defense under Contract No. FA8702-15-D-0002 with Carnegie Mellon University for the operation of the Software Engineering Institute, a federally funded research and development center. The view, opinions, and/or findings contained in this material are those of the author(s) and should not be construed as an official Government position, policy, or decision, unless designated by other documentation. References herein to any specific commercial product, process, or service by trade name, trademark, manufacturer, or otherwise, does not necessarily constitute or imply its endorsement, recommendation, or favoring by Carnegie Mellon University or its Software Engineering Institute. This report was prepared for the SEI Administrative Agent AFLCMC/AZS 5 Eglin Street Hanscom AFB, MA 01731-2100. NO WARRANTY. THIS CARNEGIE MELLON UNIVERSITY AND SOFTWARE ENGINEERING INSTITUTE MATERIAL IS FURNISHED ON AN "AS-IS" BASIS. CARNEGIE MELLON UNIVERSITY MAKES NO WARRANTIES OF ANY KIND, EITHER EXPRESSED OR IMPLIED, AS TO ANY MATTER INCLUDING, BUT NOT LIMITED TO, WARRANTY OF FITNESS FOR PURPOSE OR MERCHANTABILITY, EXCLUSIVITY, OR RESULTS OBTAINED FROM USE OF THE MATERIAL. CARNEGIE MELLON UNIVERSITY DOES NOT MAKE ANY WARRANTY OF ANY KIND WITH RESPECT TO FREEDOM FROM PATENT, TRADEMARK, OR COPYRIGHT INFRINGEMENT. [DISTRIBUTION STATEMENT A] This material has been approved for public release and unlimited distribution. Please see Copyright notice for non-US Government use and distribution.

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Copyright 2024 Carnegie Mellon University.

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