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Chemical research has reached a point where the complexity and quantity of data are too great for manual human analysis. Enter the machines. Artificial intelligence is not only becoming an integral part of data analysis but also emerging in other parts of the research workflow, including experimental design and execution. This revolution will be examined broadly but with a particular emphasis on the U.S. Department of Defense, where these technologies are uniquely capable of supporting dynamic and unconventional applications. This chapter will discuss progress in computer-aided synthesis planning (Section 6.1), challenges acquiring and working with chemical data for machine learning (Section 6.2), potential solutions to these challenges (Section 6.3), and their integration into the research workflow (Section 6.4). It is not intended to be a comprehensive review but rather a survey of the emerging challenges and opportunities through the lens of recent research.

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