DBTB INT Scott Waterman
summary
Argues that treating text as technology—not static documents but artifacts tied to computation—lets web-scale pipelines and search indexers reveal relations humans never saw before. Describes building systems that grind large web corpora into searchable graphs, using machine learning and indexing to surface new semantic links, and running experiments that show dynamic, evolving text signals outperform static corpora for discovery. Emphasizes web-scale computation and collecting novel datasets as core methods.
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