Why NLP is hard

Computers have standardized and structured data like database
tables and financial records so they are able to process the data
much faster than humans. Whereas humans use to communicate
with words that are in the form of unstructured data.We use
C++,Java or python languages to program the computers with the
set of rules that should be operated by.With unstructured data,
even these rules are quite abstract and challenging to define
concretely.
Natural Language processing (NLP) is a sub-field of Artificial
Intelligence used to get computers to understand and process
human languages.The process of reading and understanding
language is far more complex than it seems at first glance.
Understanding what a piece of text means in the real-world is very
hard.
In recent advances Machine Learning (ML) has enabled computers
to do quite a lot of useful things with natural language.Deep
Learning has enabled us to write programs to perform things like
language translation, semantic understanding, and text
summarization.
The libraries and tools that support NLP are spacy docs and textcy
docs.
The applications of NLP include language translation, chat bots,
and intricate analyses of text.