What is Artificial Intelligence (AI)? A simple explanation
Introduction
Artificial Intelligence is the development of complete systems that are capable of performing tasks that normally require human intelligence, such as decision making, object detection, solving complex problems, and so on.
The most real-life example will be personalized Google search recommendations and Facebook content. Have you ever wondered, how you keep scrolling down one video after another for hours without getting bored on Facebook or YouTube? According to a study, an average person spends about 2 hours 16 minutes daily on social media.
So yeah, AI is doing great in keeping you engaged for hours by recommending content that you might be interested in.
If you Google “Artificial Intelligence”, you will find two more terms quite often. “Machine Learning” and “Deep Learning”. We won’t go much deep into it for now. Let’s understand it with a visual representation.
This looks quite simple, but AI doesn’t end over here. It is much broader and gets really complex as well as interesting, as you go deep into it.
Why Artificial Intelligence is such a hot topic?
If you are curious about, who actually brought this concept of making machines think like humans…you will have to go back to the mid-20th century. In 1950, Alan Turing (a British mathematician, computer scientist) published a landmark paper in which he speculated about the possibility of creating machines that think.
After that, a lot of breakthroughs happened over the years, and here we are in the 21st century. So actually, Artificial Intelligence has been with us for a long time. In fact, in 1997 an AI called Deep Blue defeated the world champion, Garry Kasparov, in Chess. That is definitely a shining example of how powerful an AI can be.
But why AI is such a hot topic now?
At the time you are reading this, big corporations like Google and Facebook have gathered an enormous amount of data from you, and they will still continue to do so. This was never possible before. The collection of such an amount of data raised serious questions on individual privacy and safety. The emergence of Digital media and worldwide connectivity just put light on this, and everybody started talking about it.
How AI is different?
Let me give you a simple example…
“…
Let myVar = “Hello World”;
console.log(myVar)
…”
- Outputs — Hello World
This is a basic code written in JavaScript, where I am telling my computer to print “Hello World”. It doesn’t ask questions like why, how, when. It simply follows my order.
Now take another example, where it has to make a decision
“…
function oddEven(x) {
if ((x) % 2 == 0) {
return “Even”;
}
else { return “Odd”; }
}
console.log(oddEven(7))
- Outputs — Odd
…”
It’s alright if you don’t understand coding. All I am asking here to my computer, tell me whether 45 is an odd or an even number? To get the result, it calculates whether the input number (45) gives out a remainder after dividing it by 2 or not. If it doesn’t give a reminder, then it’s an even number, otherwise, it is an odd number.
Now, this is not an AI. It is a simple demonstration that your computer can take logical decisions.
When we speak about Artificial Intelligence, we refer to machines that can learn on their own, like you don’t have to teach an AI how to play monopoly. It can learn and take decisions on its own. The main component behind any AI is Data. It is the foundation upon which an AI is built.
Let me tell you what happens when you say to Google, “Hey Google, what is the temperature outside?”
First, the sound waves get recorded into electrical signals and then reach Google’s server. Then with Machine learning and Deep learning, the AI converts those electrical signals into words. Next, with natural language processing, it understands what am I trying to say. After that, it connects to the API from where it is going to collect data about the weather. Finally, it gives you the result.
Types of Artificial Intelligence
As discussed earlier, AI is built upon data. That is why Artificial Intelligence is categorized into 4 types –
- Reactive Machine AI
Reactive Machine AI includes machines that operate solely based on the present data, taking into account only the current situation. Reactive machines AI cannot form inferences from the data to evaluate their future actions. It has a narrow range of predefined tasks.
Example — “Deep Blue” the AI which defeated world champion Garry Kasparov (1997) in chess. - Limited Memory AI
Limited memory AI can make informed and improved decisions by studying past data from its memory. Such an AI has a short-lived or temporary memory that can be used to store past experiences and hence evaluate future actions.
Example — Self Driving cars uses the data collected in the recent past to make immediate decisions. - Theory of Mind AI
The theory of mind AI will focus mainly on emotional intelligence so that human beliefs and thoughts can be better comprehended. This has not been developed yet, but rigorous research is going on. - Self-Aware AI
The self-aware AI includes machines that have their own consciousness and can become self-aware. This type of AI doesn’t exist.
Domains / Branches of Artificial Intelligence
If you are really willing to know, how broad AI is…just read an article on Wikipedia about different branches of Artificial Intelligence. It is impossible to go through each of the branches on this blog. That is why we are categorizing all into 6 different sections –
- Machine Learning
Machine Learning is the science of getting machines to interpret, process, and analyze data in order to solve real-world problems.
The main idea behind machine learning is, giving computers the ability to learn things on their own. Like showing different images of a cat to teach itself that it is a cat. - Deep Learning
Deep learning is a particular kind of machine learning that is inspired by the functionality of our brain cells called neurons which led to the concept of artificial neural network.
The most common example of Deep Learning you can find is, Self-Driving cars like Tesla. Through its neural network, it can process its previous data and takes necessary action more efficiently. - Natural Language Processing
It refers to the science of drawing insights from natural human language in order to communicate with machines. For example, Twitter uses Natual Language Processing(NLP) to identify terrorist speech.
The same goes for Google Assitant, Siri, Alexa, and Cortana, which uses both NLP and Deep Learning to understand your voice and take necessary action. - Robotics
Robotics is a branch of Artificial Intelligence that focuses on different branches and applications of robots. AI robots are artificial agents that act in the real world environment produced results by taking some accountable actions. - Fuzzy Logic
Fuzzy logic is a computing approach that is based on the principle of the degree of truth instead of the usual modern logic that we use which is basically a boolean (True/False) logic.
Fuzzy logic is used in medical fields to solve complex problems that involve decision-making. It is also used in automating gear systems in cars. - Expert System
Expert system is a computer-based AI system that learns and reciprocates the decision-making ability of a human expert. Expert systems use if/then logic notions in order to solve any complex problems. They do not rely on conventional procedures programming.
Expert systems are mainly used in information management, like fraud detection, virus detection, also managing medical and hospital records, and so on.
