Open-Source Assessments of AI Capabilities: The Proliferation of AI Analysis Tools, Replicating Competitor Models, and the Zhousidun Dataset
<|reference_start|>Open-Source Assessments of AI Capabilities: The Proliferation of AI Analysis Tools, Replicating Competitor Models, and the Zhousidun Dataset: The integration of artificial intelligence (AI) into military capabilities has become a norm for major military power across the globe. Understanding how these AI models operate is essential for maintaining strategic advantages and ensuring security. This paper demonstrates an open-source methodology for analyzing military AI models through a detailed examination of the Zhousidun dataset, a Chinese-originated dataset that exhaustively labels critical components on American and Allied destroyers. By demonstrating the replication of a state-of-the-art computer vision model on this dataset, we illustrate how open-source tools can be leveraged to assess and understand key military AI capabilities. This methodology offers a robust framework for evaluating the performance and potential of AI-enabled military capabilities, thus enhancing the accuracy and reliability of strategic assessments.<|reference_end|>
@article{gupta2024open-source,
    title={Open-Source Assessments of AI Capabilities: The Proliferation of AI
  Analysis Tools, Replicating Competitor Models, and the Zhousidun Dataset},
    author={Ritwik Gupta, Leah Walker, Eli Glickman, Raine Koizumi, Sarthak
  Bhatnagar, Andrew W. Reddie},
    journal={arXiv preprint arXiv:2405.12167},
    year={2024},
    archivePrefix={arXiv},
    eprint={2405.12167},
    primaryClass={cs.CY}
}