A county grants office wants to tag incoming PDF narratives by research theme so reviewers can sort the pile. The files are prose, not photos and not sensor streams. Which capability should they use?
Select an answer to reveal the explanation.
Short Explanation
Think of it like a librarian reading the grant and slapping a theme sticker on the folder. The PDFs are prose, so natural language processing is the capability that tags the pile. Vision is for photos, forecasting is for numbers over time, and a robot arm is for moving things, not sorting sentences.
Full Explanation
Natural language processing is the capability of machines interpreting human-language text, which is what theme-tagging of grant narratives requires. Computer vision interprets pixels, not prose. Time-series forecasting predicts future numeric values from ordered measurements. A robot-arm policy is a control task and does not classify document themes.