Machines can read, but do they understand?
A novel NLP application built on a Google transformer model can help predict ratings transitions
In the quest to give human abilities to machines, reading text and assimilating its context is a crucial step. Understanding spoken or written language allows machines to process large amounts of unstructured data such as news or documents—freeing humans from the billions of hours of drudgery necessary before they can be used to inform decision-making.
The theoretical foundations for natural language processing (NLP), a branch of artificial intelligence that studies how to process textual data
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