Natural Language Processing in the 21st Century

Source: Deep Learning on Medium

Natural Language Processing in the 21st Century

In the 21st Century, where the world is moving towards automation. The minds of the people are getting more intelligent day by day. The use of computation is getting increase at a high rate. Everyday, automated things are coming in our lives to make it more easier and better. Such as Google Assistant, Self Driving cars, AI in out systems etc. All these technologies includes Artificial Intelligence or Machine Learning or Deep Learning.


Today almost every gadget uses Artificial Intelligence or ML now a days, as they are gaining hype in the field of Computer Vision ,Data Science ,Natural Language Processing , Data Engineering , Cloud Computing etc. As this blog is about Natural Language Processing, so we discuss the use of NLP and it’s promises in the field of Ai.


In general terms the NLP( Natural Language Processing) is the manipulation of Text, Speech etc through computational power by using various software.

In the field of Artificial Intelligence, we have it’s sub part, which we refers to Deep Learning. Deep Learning is used to create Artificial Neural Networks which mimics as our brain. DL is playing a vital role in the field of Computer Vision, Data Science and Analytics and especially in Natural Language Processing. The manipulation of the text or speech is done through the ANN, where we put a lot of data into the network, where it train itself and generates some results.

The Text or Word, can be found every where on the internet. Such as






There are lot more then these examples, but you have to dig the internet. The more you dig it the more you will find good results.


“It is hard from the standpoint of the child, who must spend many years acquiring a language … it is hard for the adult language learner, it is hard for the scientist who attempts to model the relevant phenomena, and it is hard for the engineer who attempts to build systems that deal with natural language input or output. These tasks are so hard that Turing could rightly make fluent conversation in natural language the centerpiece of his test for intelligence”

— Page 248, Mathematical Linguistics, 2010.


The term computational linguistics is used when you combine the linguistics with the computational power, combining it with computational tools. If if go back before 2000, the concept of Machine Learning and Deep Learning had been introduced but there weren’t any resources through which we can apply these concepts, which we known as the Winter Age of Artificial Intelligence. Now, in this era, where we have high computational power such as high performance GPUs and we have a huge amount of data, so we can now apply some very complex algorithm on the text or voice data which requires high performance of processing. As DL adds speed, robustness and more accurate results versus the traditional approach which were used a decade ago or more than it. The use of Natural Language Processing is gaining it’s potential at a high rate, which is a positive sign in the field of Artificial Intelligence.

“The voice that navigated was definitely that of a machine, and yet you could tell that the machine was a woman, which hurt my mind a little. How can machines have genders? The machine also had an American accent. How can machines have nationalities? This can’t be a good idea, making machines talk like real people, can it? Giving machines humanoid identities?”

Matthew Quick, The Good Luck of Right Now