Technical details of Machine ReadingMRC requires modeling complex interactions between the context and the query. Using a novel neural network architecture called the, researchers were able to mimic the inference process of human readers.With a question in mind, ReasoNet reads a document repeatedly, each time focusing on different parts of the document until a satisfying answer is found or formed. Microsoft researchers today have been able to surpass human-level parity on dataset using an unique MRC algorithm called: Machine reading comprehension with self-matching networks. R-NET applies a self-matching attention mechanism to refine the representation by matching the passage against itself, which effectively encodes information from the whole passage.When we applied these MRC algorithms to the book, by Brad Smith and Harry Shum, it was incredible to see that we can answer so many interesting questions. We can apply this to solve enterprise data challenges and answer enterprise domain specific questions.

Aug 21, 2019  Dr. Mudrunner free download. Hazen has spent much of his career working on machine speech and language understanding. Hear why reading comprehension is so hard for machines and get an inside look at the technical approaches being used to tackle the problem.

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