What Is Artificial Intelligence And What Are Its Uses?

What is Artificial Intelligence

The term “Artificial Intelligence” seems to be in vogue nowadays. Elon Musk, Jeff Bezos, and Google have invested heavily into this technology and POTUS Donald Trump just signed an Executive Order pledging governmental support to AI development. But what is this futuristic technology that claims to assist us in all walks of life in the near future? How does it work? And what does it mean for a computer to ‘learn’? Read ahead to find out.

What is AI?

To understand Artificial Intelligence, one must first understand the limitations of computers. At its core, a computer is a machine that can do calculations very fast and accurately, repeatedly. This is why computers have found widespread use in the modern world. They are useful in carrying out both monotonous and complex tasks.

However, every computer needs to be fed with instructions. The process of feeding the computer with instructions is known as programming. Programmers write instructions in different programming languages such as C, C++, Java, Python etc. Programming can be quite complex because computers can only execute one instruction at a time. Granted, modern computers can do this very fast, writing code that makes a computer do exactly what you want it to do is a coveted skill in this age.

The predecessor to writing code is designing an algorithm. An algorithm is a set of instructions that describes how to solve a problem. A good programmer is able to design an efficient algorithm and write it in a language the computer can understand. Due to the advances in computer science, we now have processors that can execute millions of instructions per second, algorithms that allow us to execute complex and monotonous tasks efficiently and, languages and interfaces that make communicating with computers quite easy.

However, despite all these advances, a conventional computer cannot make its own decisions. A computer with a flawed algorithm will in fact produce incorrect results. A computer is incapable of learning from experience. This is where the term ‘Artificial Intelligence’ comes in.

AI is a special type of algorithm that is capable of learning i.e. adapt, reason and provide solutions. Let’s take the example of a bipedal robot. If the robot is simply programmed to walk, it will function correctly until it encounters a turn or an obstacle. However, if equipped with AI, over time, it will learn to identify obstacles and turn when required. In a general sense, this is incredibly useful, as this robot will theoretically be able to walk on all types of terrain without having to be programmed separately for every scenario.

For this very reason, AI has become such an important focus of research today. It is being integrated into smartphones, cars, banking, surveillance, manufacturing, medicine and many more industries. It has the potential to be used in every possible industry. The aim of employing AI technology is to reduce human supervision and increase the level of automation. AI is being trained to make decisions that were previously taken by humans.

Types of AI

Based on the level of human supervision there are two types of AI:

Weak AI

Their capability to learn is limited. They can only simulate actual decision making. An example of weak AI would be the range of digital AI assistants such as Google Home and Alexa available today. You can tell Alexa to switch off the lights but, your instruction is executed because Alexa has been trained to identify the words ‘switch’ and ‘off’

Strong AI

This type of Artificial Intelligence simulates a biological brain. It is capable of observing and learning over time. AI seen in games is an example of Strong AI. AlphaGo is an AI developed by the company Deepmind. This AI is designed to play Go, a Chinese board game. It is played with black and white pebbles with the aim of capturing all your opponents’ pebbles. Go, while appearing simple, is a game of complex strategy. In 2015 AlphaGo became the first computer to beat a professional Go player, without handicap. This is especially remarkable because many algorithms have been created in the past to play Go but none could beat the factor of human intuition till AlphaGo. This is because of AlphaGo’s ability to learn from repeated experiences.

 Apart from the level of human supervision, AI can also be categorized by their function:

Specialized AI

This type of AI has been designed for a specific task. For example, driving a car. Uber recently debuted their self-driving cabs.  The AI in these cars has been specifically trained to identify the road, other cars, markings, barriers and pedestrians and then make decisions to navigate safely through these elements.

General AI

This kind of AI is capable of doing more than just one specialized task. The aim of developing better General AI is to further reduce the amount of human intervention required for a computer to adapt, observe and learn.

Uses of AI

While AI solutions can be implemented in virtually all industries, quite a few industries have already started using it.


In an industry which is facing labour shortages, employing AI solutions can help increase efficiency and production. AI-controlled systems can automatically analyse and compensate for changes in conditions of the soil, humidity, temperature and regulate the use of water. It can boost the efficiency of the process by allocating resources more accurately. It can help foster farming practices which boost production and are sustainable for the ecosystem at the same time.

Customer Service

Maintaining good relations with existing customers is an important part of every business strategy. Keeping your customers happy will give a better return in the future. From chatbots to recommendation algorithms on your favourite streaming services, AI is running the show. Chatbots are being increasingly used to automate customer queries. Apart from being able to communicate simply replies, it can transfer to a human operator if needed. Spotify’s famed recommendation algorithm owes its popularity to AI.


AI can be used to predict diseases. Yes, by analyzing the patients’ health history, results of tests and genetic data, AI can predict the chances of a patient contracting various diseases including cancer. Analyzing the patient’s DNA allows AI to identify at-risk patients, formulate predictive cure solutions and customize care for patients.


Did you know, products in supermarkets are strategically placed based on studying customer behaviour? For example, the most in-demand products are kept towards the back of the store to encourage the consumer to spend more time in the store. Optimizations such as this can be provided by an AI that analyses data. Keeping track of inventories, sales and even billing can be handled by AI systems. Online retailers use AI to recommend products to customers and analyse ratings and reviews of products to determine bestsellers. It also helps in optimizing delivery mechanisms.


Improving Automation is always a priority for the manufacturing industry. AI can be used to automate a variety of manufacturing processes including quality testing, supply chain and distribution chain, robotics and maintenance. AI can analyse the data generated from these processes to project sales volumes, estimate the amount of raw materials required and even provides solutions to increase efficiency.

Transport and Logistics

This industry has the potential of improving efficiency exponentially with the implementation of AI. From self-driving cars to smart ports, AI has already made a mark on this industry. AI is now capable of scheduling, managing and analysing data generated from seaports, truck terminals and airports to maximize the efficiency of transport and delivery systems.


To summarize, Artificial Intelligence is a special type of algorithm that allows computers to learn, adapt and make decisions. AI is being rapidly integrated into our daily lives as industries are embracing this technology and reaping its benefits. AI reduces the amount of human involvement needed in a process hence, reducing the rate of errors, optimizing the efficiency of the process and some times, even providing solutions to improve it.