RPA Solution Architect's Handbook by Sachin Sahgal

Author:Sachin Sahgal
Language: eng
Format: epub
Publisher: Packt
Published: 2023-01-15T00:00:00+00:00

NLP

With the advancement of ML, NLP has gained a lot of traction and become one of the most sought-after technologies from the ML stack. It helps in understanding the context, meaning, and language itself. Nowadays, NLP can understand English and other languages such as French, German, Spanish, and Danish. Having this capability at our disposal expands the horizon of IA and the type of processes that can be automated using IA. While NLP can understand and recognize the language, natural language understanding (NLU) is what helps in understanding the meaning of the sentence or text. This helps the machine to understand the context. Once we teach the machine to understand, we can also teach machines to construct meaningful full replies based on the understanding. This technology is called natural language generation (NLG). Now, with all these three combined, you can achieve human-like behavior where you can extract the data using OCR, detect the language and understand it using NLP and NLU, and then compile a reply based on NLG. This is how human intelligence is being replicated to an extent in today’s words of automation. There is a plethora of use cases in every industry that is benefiting from the use of these technologies. Now, humans don’t have to read and go through thousands of written documents to extract the meaning of the document or find errors and mistakes. Machines can do that for humans in a fraction of a second compared to humans doing the same in hours.

This concludes the list of components used in designing an IA solution. Now let’s see how these components can be used to design an IA solution and what considerations should be kept in mind while designing such solutions.

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