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Artificial Intelligence (AI), the most hyped technology of the 21st century, has made a big impact in virtually every industry. When we hear the word AI, we generally think of a world full of robots and self-driving cars, but this picture of AI hides its major practical applications in the real world. So this blog is here to give you a clear picture of what AI is and how it works. Let’s begin.
What is Artificial intelligence?
Artificial Intelligence (AI) is a vast field of computer science being developed with the motive of building smart machines that could swiftly perform tasks that require human intelligence with more precision. AI is a simulation of natural intelligence in which machines are programmed such that they can learn with experience and mimic human actions. For example, a robot could be programmed in such a way that it could learn how to walk and navigate through obstacles just like a human.
The need and purpose of AI
Just like any other technology at its core, AI is also developed to reduce human effort and improve speed and accuracy to complete tasks more efficiently by automating them and generating more accurate results. Currently, in the present world, an average of 25 quintillion bytes (1000 petabytes) of data are generated every day, and it's almost impossible for humans to process and analyse such vast amounts of data because of the limitations of human cognitive ability. So here is where the major role of AI comes into play, i.e., data processing. AI systems interpret the raw data by analysing it to sort the complex data and extract meaningful predictions from it for more reliable decisions to complete the task.
The most common example of this that we come across daily is Google’s search engine. Google’s predictive search algorithm uses past user data to predict what a user will type text in the search bar. It also shows ads on websites based on the user's past web activity. Another popular use case for AI is chatbots like ChatGPT and voice assistants like Alexa and Siri. In this case, AI is used to hold a conversation like real human beings.
Origin and History of AI
Believe it or not, the idea of machines that could think and reason like humans goes back thousands of years. Ancient Greek myths and legends are full of stories about machines that could perform tasks on their own, like Talos, the giant bronze automaton that protected the island of Crete. However, the story of modern AI technology began in the mid-twentieth century. Following World War II, scientists and engineers sought ways to apply the most recent technological advances to a wide range of fields, including computing.
The 1950s saw the concept of AI being realised in full swing since many advances in the field of AI came to fruition at this time. The first major success in this decade was when Alan Turing, a famed mathematician, proposed "The Imitation Game." According to Turning, a machine that could converse with human beings without them knowing it was the machine would win this "imitation game" and could be perceived as intelligent." This proposal went on to become "The Turing Test," which became a measure of machine (artificial) intelligence.
However, the greatest success arguably in this decade was when computer scientist John McCarthy arranged the Dartmouth Summer Research Project at Dartmouth College in 1956. The term "artificial intelligence" was coined at this conference by McCarthy. In the early days of AI, researchers focused on creating programs that could perform simple tasks, such as playing chess or solving mathematical problems. These programs were based on a concept called "symbolic AI," which used rules and logic to make decisions.
In 1956, Allen Newell and J.C. Shaw created "Logic Theorist," one of the first AI programs. The program was able to prove mathematical theorems using symbolic logic, demonstrating that computers could perform tasks traditionally reserved for human intelligence. A year later, Arthur Samuel, a computer scientist at IBM, coined the term "machine learning" when he was speaking about building a computer that could play a game of chess much better than the person who programmed it.
What do AI systems comprise?
At a basic level, AI systems comprise or require three major components to perform tasks that require human intelligence like image or pattern recognition, decision making, etc. These components are:
Algorithms: An algorithm is a set of instructions that tells a computer what to do. In the case of AI, these instructions are designed to mimic human thought processes and decision-making. There are many different types of algorithms used in AI, including decision trees, neural networks, and support vector machines.
Data: To learn and improve over time, AI systems require large amounts of data. This data might come from a variety of sources, such as medical records, social media feeds, or sensor data from Internet of Things (IoT) devices. The more data an AI system has access to, the better it can learn and make predictions.
Computational power: AI systems require powerful computers and specialised hardware to perform the complex calculations necessary to make decisions and predictions. This might include things like graphics processing units (GPUs) or tensor processing units (TPUs), which are designed specifically for AI workloads.
Once an AI system has access to algorithms, data, and computational power, it can start to learn and make predictions. For example, a computer vision system might be trained on thousands of images to learn how to recognize specific objects or patterns. Similarly, a natural language processing system might be trained on millions of text documents to learn how to understand and respond to human language.
What's next
We're just getting started with exploring artificial intelligence. So far, we've talked about what AI is, why it's important, and looked at its history. We've also checked out the basic parts of an AI system to understand how it works. But wait, there's more! In the next part of the series, we'll dive into different fields of AI and how AI systems work. Stay tuned, keep learning, and keep exploring!
