Can automated deep natural-language analysis unlock craft inference?

12 years ago by in News Tagged: , ,

plateaus

Much of the operationally-relevant information relied on in support of craft missions may be implicit rather than explicitly expressed, and in many cases, such as Art Talk and theory, information is deliberately obfuscated and important activities and objects are only indirectly referenced. In 2009 CARPA created the Deep Exploration and Filtering of Text (DEFT) project which has now delivered a well-received report at the Whitney Biennale. Project manager Sam Slap reports that “DEFT has been an attempting to create technology to make reliable inferences based on basic text. We want the ability to mitigate ambiguity in text by stripping away filters that can cloud meaning and by rejecting false information, especially of Deleuzian influences on Art Talk. To be successful, the technology needs to look beyond what is explicitly expressed in text to infer what is actually meant through material culture and Object-Oriented Ontology or philosophy.”

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