NLP or Natural Language Processing is a field of study within computer science and linguistics that tries to understand and interpret how humans understand each other or even give responses.

Examples of natural languages include English or Chinese. Natural languages enables communication in an easy and intuitive way between humans.

But what if computers could understand that language? That is the main goal of NLP.

We will be using the English language as a common ground to start building our knowledge.

Applications

Chat bots news are out the roof with the recently release chat GPT bot that can generate well written sentences from user input. This is an application of NLP, get user input then respond in the same language.

Applications of chat bots are almost, if not, endless. From medicine to architecture, it revolutionizes the industry.

But NLP is not just chat bots, it can also aid in human conversations, by translating what a person says and presenting the output to the other person.

I could talk about where you can apply NLP my whole life since this field is so wide.

The complexity in natural language

As talked before natural language is highly complex and variable, making it challenging for computers to process and understand.

This way, NLP presents a challenge to the modern days, but the constant advancements are helping to improve the performance and enable them to fair better in human conversations.

Below are some challenges inherent of the natural language.

Context dependence

The meaning of words and phrases often depends on the context in which they are used.

For example, the phrase “I’m beat” could mean that someone is tired, or it could mean that someone has been beaten in a fight. Disambiguating the meaning of words and phrases in a certain context is a key challenge for NLP systems.

Syntactic and lexical ambiguity

Syntactic ambiguity refers to the fact that the same sequence of words can be interpreted in multiple ways depending on how they are arranged into phrases and clauses.

For example, the sentence “The old man the boat” is syntactically ambiguous because it is not clear whether “the old man” is the subject or the object of the verb “the boat.”

Lexical ambiguity refers to the fact that a single word can have multiple meanings in different contexts.

For example, the word bass can refer to a type of fish or a low-frequency sound.

Disambiguating lexical ambiguities is often a key task in NLP, as it is necessary for the correct interpretation of the text so there are no misunderstandings.

Both syntactic and lexical ambiguities are challenging for NLP systems because they require the system to consider multiple possible interpretations and to choose the most appropriate one based on context and other clues that are not that trivial.

Idiomatic expressions

Natural language is full of idioms and expressions that can be difficult for NLP systems to decipher. For example, the phrase “break a leg” is an idiom that means “good luck,” but it would be rather difficult for an NLP system to infer this meaning from the individual words.

Vagueness and imprecision

Natural language is often vague and imprecise, which can make it difficult for NLP systems to extract precise meaning from text. For example, the phrase “a little bit” could mean a very small amount, or it could mean a moderate amount.

Conclusion

Despite the multiple challenges, NLP will revolutionize the world and the way we think about text and the languages.

In summary, NLP is a fascinating and important field that aims to enable computers to understand and process our human language. By using techniques from fields like linguistics and machine learning, NLP systems can extract meaning from text.

And with that information you could perform a wide range of tasks that involve understanding and processing language.

As NLP continues to advance and studies are made in this topic, it will assume a role of major importance in how we do our daily activities and how we interact with technology.

As such, although AI will not replace us in the foreseeable future, it will certainly change our lives for better and provide help on harder problems.