What is Artificial Intelligence? 

Before understanding Artificial Intelligence, it is important to have at least a generalized view of what is mean by intelligence itself. In simple words, intelligence is nothing but human behavior, of course, animals also consist and exhibit the same intelligence and IQ levels depending on the species of the animal.

Nonetheless, all the activities demonstrated by humans and animals in their daily lives are termed as the display of intelligence. (Ruhl, 2020)

After learning the meaning of intelligence as a whole it becomes easy to understand what is mean by Artificial intelligence. Artificial Intelligence is a self-explanatory term, it refers to intelligence displayed by machines rather than humans and animals.

It is the ability of computers or any automated machines to demonstrate the tasks that normally done manually. With Artificial intelligence.

Machines are equipped with the acumen to process like humans only for example, in the contemporary world with technology prevailing.

computers and machines have in-built features of reasoning, discovering, and understanding what was previously associated with living organisms only. (Copeland, 2021)

Branches of Artificial Intelligence

Like any other vast field of study involving this level of complexity, Artificial Intelligence is also divide into different branches to better recognize the features and characteristics of each type of artificial intelligence and its specialties. Following are the main branches of artificial intelligence;

1. Experts Systems

2. Machine Learning 

3. Neural Network

4. Robotics

5. Natural Language Processing

6. Fuzzy Logic

Each branch is different from the other and has its own distinctive features for example; (Roger, 2021)

• Expert systems: It is the type of artificial intelligence that learns to emulate the decision-making abilities of humans. 
• Machine Learning: It is the most widely demanded field of artificial intelligence as it is a self-improving branch of AI to provide the solutions and results by analyzing the situation itself.
• Neural Network: Also goes by the name of ‘Deep learning’ is associated with cognitive science and neurology helping the computers to realize the required task.
• Robotics: As the name suggests, this branch of artificial intelligence is associated with the designing, structuring, and operating of robots with the help of science, mathematics, and engineering. 
• Natural Language Processing: It is a very interesting innovation in the field of artificial intelligence that is to understand the texts and language of humans as they write and speak to better assist them.
• Fuzzy Logic: This branch of AI deals with the rectification and modification of ambiguous data to help computers and humans in reasoning.    

Among all the branches of Artificial Intelligence, Machine Learning (ML) and Natural Language Processing (NLP) are the ones that have higher levels of significance in the technology industry due to their unique characteristics.

What is Natural Language Processing (NLP)

As briefed above NLP is a processing language design to assist humans’ using computers in an improved manner. Back in the 1940s when digital computers were first launch, it only understood the numeric language that also the specific language of binary codes specially designed for computers.

This language being alien to humans made instructing the machine difficult thus, building a gap between the two. To reduce the dissimilarities, in the 1950s Natural Language Processing. NLP was introduced that would decipher the natural language of humans like speech and text using software for automatic maneuvers. 

However, it is far more profound than it seems. After the emergence of the language common between humans and computers,

it was important to evaluate the ability of each new machine invented that is to what extent they can understand the commands and for that purpose, Alan Turing initiated a now called Turing test to examine the machine’s ability to be equivalent or better than human intelligence. (Canuma, 2019)

How does Natural Language Processing (NLP) work?

NLP makes it easier for the computer to understand the human language but how does it work? The software is develop in a manner that understands the grammar rules, the structure of sentences, and the meanings of all the words used. After comprehending the words, the system uses a special algorithm to put out the result of the question. All the commands given to the machine are first convert into binary codes that are understandable to the computer, then after the processing at the back end, the result is also convert from binary to human language for their comprehensibility. All of this is done in seconds with the help of Artificial Intelligence. 

The most common examples of NLP could be Alexa, Siri, and Google Assistant that recognizes the speech and assists accordingly. (Roldós, 2019) 

These facilities other than businesses have also enabled students to make the most out of it by getting custom assignment help related to any topic they have easing the tough schedules of full-time students. 

What is Machine Learning?

Natural Language Processing and Machine Learning are closely related, and sometimes used interchangeably however, both of them are different from each other with have slight but significant variations.

Technology Learning first introduced in the 1950s, when Arthur Samuel noticed that the more the self-playing chess system played the game, the better it became, therefore, giving birth to Machine Learning.

Machine Learning is that branch of artificial intelligence that has the ability to self-improvise without any man-made maneuvers or additions to the system. Machinic Learning uses an algorithm that enables the machine to decipher the subliminal meanings from the data and progress over time.

In simple words, it can be said that Machine Learning (ML) is that branch of Artificial Intelligence that learns from experiences thus, imitating the human feature of intelligence. 

How NLP and ML are different?   

As mentioned above that NLP and ML are closely related, it is imperative to understand that NLP works with languages that how computers and other automated machines understand the human dialects and texts, process them to make sense to the computer, and perform the tasks like translations.

Search results, cheap assignment writing services, and similar stuff. On the other hand, ML uses algorithms that teach the machines to learn and improvise automatically without any manual programming.

Consequently, to have better results from Natural Language Processing, Machine Learning is applied. 

Thus, Artificial Intelligence is an umbrella term under which both Natural Language Processing (NLP) and Machine Learning (ML) fall. Both the categories linked with each other and require each other to perform their respective functions smoothly.  

References

Canuma, P. (2019, 30 August). The brief history of NLP. Retrieved from medium.datadriveninvestor.com: https://medium.datadriveninvestor.com/the-brief-history-of-nlp-c90f331b6ad7

Copeland, B. (2021, December 14). Artificial Intelligence. Retrieved from Encyclopedia Britannica: https://www.britannica.com/technology/artificial-intelligence

Roger, S. (2021, February 22). What are the branches of Artificial Intelligence? Retrieved from h2kinfosys.com: https://www.h2kinfosys.com/blog/what-are-the-branches-of-artificial-intelligence/

Roldós, I. (2019, June 9). NLP, Machine Learning & AI, Explained. Retrieved from monkeylearn.com: https://monkeylearn.com/blog/nlp-ai/

Ruhl, C. (2020, July 16). Intelligence: Definition, Theories and Testing. Retrieved from simplypsychology.org: https://www.simplypsychology.org/intelligence.html