As artificial intelligence progresses and technology becomes more sophisticated, we expect existing concepts to embrace this change — or change themselves. Similarly, in the domain of computer-aided processing of natural languages, shall the concept of natural language processing give way to natural vocabulary understanding? Or is the relation between the two concepts subtler and a lot more complicated that merely linear progressing of a technology?
In this post, we’ll scrutinize over the ideas of NLP plus NLU and their niches in the AI-related technology.
Importantly, though sometimes used interchangeably, they are actually two different concepts that have some overlap. First of all, they both deal with the relationship among a natural language and artificial intelligence. They both attempt in order to make sense associated with unstructured data, like language, as opposed to structured data like statistics, actions, etc. However , NLP and NLU are opposites of a lot of other information mining techniques.
Natural Language Processing
NLP is an already well-established, decades-old field operating at the cross-section of computer science, synthetic intelligence, and increasingly data mining. The ultimate of NLP is to read, decipher, understand, plus make sense of the human languages by machines, taking certain tasks off the humans and allowing for a machine to handle them instead. Common real-world examples…
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