Analysing the Difference between AI, Machine Learning and NLP

Do you ever think what makes technology so crucial in our life?

Well, the contribution of science and technology is simply undeniable. We can’t overlook its importance or application in our daily life. It not only saves our time but also minimises our efforts.

Artificial Intelligence, Machine Learning and Natural Language Processing are the most trending and cutting-edge technologies. Most often, people get confused with the concept of these three terminologies. Majority of us often think Artificial Intelligence and Machine Learning both are the same. However, in reality, it is not like that.

Well, to resolve the doubts or to clear up confusion, we are going to discuss the differences between AI, ML and NLP. The major differences will help you better understand how these technologies differ from each other.

Artificial Intelligence

Let us first discuss Artificial Intelligence. It is a combination of two terms, i.e. artificial and intelligence. It means something that is not real yet intelligent. We can define it as the creation of an intelligent machine that can work or function like humans. The main objective of AI is to create an intelligent system that can learn and perform difficult tasks.


Currently, AI is becoming a game-changer in the fields of healthcare, finance, agriculture, gaming, chatbots, autonomous vehicles, data security, and a lot more.

  • Self-Driving Cars: An autonomous vehicle is equipped with sensors and software helping you navigate to your destination without human operator or input.
  • Computer Vision: A machine or robot responds to visual images or videos.
  • Facial Recognition: AI identifies or detects faces by names.
  • Humanoid Robots: Structurally similar to humans and carry out functions through sensors and actuators.
  • Gaming: AI machine is also used for strategic games like chess.

Machine Learning

It is a subfield of artificial intelligence. As the name suggests, a machine learns to perform different tasks in this field. Yes, to function or act intelligently, machines are required to learn like humans. Let us understand how machine learning works. A data is fed into the machine as input and based on this data, the machine can learn to do different tasks. In simple words, we teach machines with data input to perform a specific task or to give accurate output.

Although it sounds like both AI and ML work like the same, it is not the case. Artificial intelligence works based on intelligence or reasoning, i.e. to solve complex problems or explore optimal solutions. However, machine learning functions based on previous experiences. Its emphasis on accuracy, rather than finding optimal solutions.


If we say ML is an incredible breakthrough in the field of technology, then nothing is wrong about that. Machine learning is no doubt doing wonders in the field of customer service, sales and marketing, Google search algorithms, healthcare, financial services, etc.

Let us have a look at a few examples of machine learning that we use, but we don’t even know that they are driven by ML algorithms:

  • Traffic predictions: GPS navigation services allow users to find their way more easily.
  • Search Results: Search engine improves or refines search results.
  • Online fraud detection: Ensure cybersecurity, i.e. protection against money laundering, cybercrimes, etc.
  • Online customer support: Live chat software offers real-time customer service.
  • Product recommendations: Products or services suggestions based on past purchases.
  • Social media services: Friend suggestions on Facebook.

Natural Language Programming (NLP)

NLP is also a subfield of Artificial Intelligence. And, we are bound to say that it is one of the most challenging and revolutionary approaches in the field of AI. You will be amazed to know that a machine can speak, listen, write, and understand human language. Yes, it is possible with NLP.

We can define NLP as a field of artificial intelligence that can enable computers or machines to not only comprehend and interpret human language but also write or speak. It is possible when we teach machines the basics of grammar and syntax or how a language works. The actual meaning of a keyword also matters a lot, because it is imperative to understand the exact word along with its meaning to give a natural response.


Natural Language Processing (NLP) is used in a wide range of applications. Here are a few of them:

  • Sentiment Analysis of a website: Identify the customer’s opinion, i.e. positive or negative regarding a specific product or service.
  • Virtual assistant applications: Siri, Alexa, Cortana, Google assistant, and chatbots, answer to the user queries.
  • Automatic summarisation: Extract accurate and short information from large chunks of text.
  • Spell or Grammar checker: Identify and correct any spelling or grammar mistake.
  • Text categorisation: Assign categories or organise information, i.e. spam filtering in email.
  • Machine Translation: Translate information from one language to another, i.e. Google Translate, Bing Translate, etc.

Well, hopefully, the differences will give you a clear idea or clear up all your confusion. You also realise how these technologies and their diverse range of applications are transforming different fields. All in all, we can say that AI and its subfields offer convenience, accuracy, speed, security and assurance to our lives.