The Three Domains of AI: Data, Computer Vision and Natural Language Processing

Hello students, welcome to Kwickprep. How does a phone read a number plate, understand your voice, or predict tomorrow's sales? Each job belongs to a different area of AI. Today we learn the three domains of AI, with an example and a free online game for each.

First, a new word. A domain means an area of work, just like science and commerce are areas of study. AI is grouped into domains by the kind of data it works with. The three kinds are numbers in tables, images and videos, and human language, spoken or written.

Here are all three domains together. Data Science works with numbers in tables, for example forecasting a shop's sales. Computer Vision works with images and videos, for example unlocking a phone with your face. Natural Language Processing, or NLP, works with text and speech, for example a voice assistant.

Let us study the first domain, Data Science. Data Science collects numbers, like marks, prices or temperatures, and studies them. It finds patterns, which means things that repeat, and trends, which means the direction numbers are moving. Using these patterns, it predicts what may happen next.

Here is an example from a small umbrella shop. In May, the shop sold only twenty umbrellas. In June, when the monsoon arrived, sales jumped to one hundred and eighty. In July, sales rose to two hundred and fifty. In August, sales stayed high at two hundred and thirty. So a Data Science model can tell the owner to stock up before next June.

Data Science is used in many places. Airlines change ticket prices by studying how many seats are booked. During a cricket match, the win predictor on screen uses past match data. Banks study your usual spending, so an unusual payment can be stopped and checked.

Now the second domain, Computer Vision. Computer Vision helps a computer understand images and videos, the way our eyes and brain do. A digital image is a grid of tiny coloured dots called pixels, and the computer only sees their number values. From those numbers, AI learns to find shapes, faces and objects.

Here are Computer Vision examples. Face unlock compares the camera image with your saved face. Some parking gates read vehicle number plates from camera images. Self-driving cars watch lanes, signals and people on the road. Farmers can photograph a leaf, and an app can spot signs of crop disease.

The third domain is Natural Language Processing, or NLP. Here, natural language means the languages people speak, like Hindi, Gujarati or English. NLP works on both written text and spoken words. It lets a computer read, translate, summarise and reply.

Here are NLP examples. A voice assistant turns your speech into text, understands it, and replies. A translation app can turn a Hindi sentence into English. Autocorrect on your phone fixes spelling while you type. A chatbot on a railway or bank website answers common questions.

Pause and predict the domain for each task. Counting cars in a traffic camera video is Computer Vision, because the data is video. Sorting product reviews into angry and happy is NLP, because the data is written language. Predicting next week's milk demand from past sales is Data Science, because the data is numbers.

Now the fun part, try one free online AI game for each domain. For Data Science, find a game that studies your past moves and predicts your next one. For Computer Vision, try a game where you show real objects to your camera and it names them. For NLP, try a game where you ask spoken questions and the computer answers in words.

While you play, think like an AI student. In the data game, check whether the AI starts winning once it learns your habits. In the vision game, notice which objects or lighting confuse the camera. In the language game, notice which questions it cannot understand, and think about why.

Let us recap. Data Science works with numbers and makes predictions. Computer Vision works with images and videos. NLP works with human language, in text and speech. And you can feel each domain by playing its game.