Artificial intelligence has been growing exponentially faster over the past decade. It has already touched our lives in many ways. For example, every time you go on Google search, some artificial intelligence is used to show you the best results. Natural language processing and speech recognition are applied every time you ask questions.
So, artificial intelligence will be one of the most significant scientific breakthroughs in the 21st century. Artificial intelligence enables us to probe the universe and go to the depths of our humanity. It uses different approaches and has the potential to change humans forever.
The backbone of artificial intelligence is machine learning, and I think the term itself is self-explanatory. We can make machines learn based on the input knowledge and enable them to make decisions. Two components of machine learning are applied. The first uses algorithms to find the meaning of data, and the second uses learning algorithms to find the relationship between the knowledge and improve the learning process.
The overall goal of machine learning is simple. It improves the performance of the machines and tasks. Artificial intelligence predicts stock markets for complex tasks like translating articles into different languages. For example, we need a Google translator when we travel anywhere or especially travel the places where we cannot understand the language. The Google translator is embedded with artificial intelligence.
Well, have you ever wondered about it? Google has over 10 to 15 Exabytes of data. Let me make it easy, Google’s 500GB of data is 30 million personal computers. And the data turns out to be one of the fuels or powers that Google translates the magical technology.
The Google translator is getting faster and more accurate than before. This self-learning and accuracy haven’t been possible due to human intervention. It is a real-world example of how machines can self-learn past experiences. The technique of learning from past experiences is referred to as experiential learning. The human brain uses experiential learning to discover new things and gathers previous experiences to do the work accurately.
Many training algorithms provide machines with some knowledge, which is taken as input by the computer. The user gives some inputs to the computer, and based on that inputs, the output or predictions are derived. So in the context of Google, the Google 15 Exabyte of data will be the training input, and the output will be some artificial language.
The learning algorithms power computers to learn and be intelligent. Let’s focus two most important aspects of artificial intelligence.
A visual signal from our retina is given to the primary visual cortex of our brain. And this visual information is separated and processed in three different processing systems. One system processes colour, the second processes shape, and the third processes movements, locates objects, and orientation.
So when image processing is done in the context of computers, the computers try to understand the image with the help of different processing units; each unit provides some information about the features of the picture. The computers process various regions of the image to give an accurate output. We can summarize it with a simple flowchart.
We input to the machine, and the machine processes the information with the help of some algorithms. The neural networks are used to improve the processing and accurately give the outputs.
Our brain is made of millions of neurons, and the tiny neurons communicate with one another and process information, which is how we become intelligent. When all this is used in a computer, it processes the same way our human brain processes information.
Let us first understand the biological and artificial neural networks. The biological dendrites, axons, cell bodies, and terminal axons get the input and process the information. Similarly, in an artificial neural network, some inputs are given to the first layer and are then processed using mathematical calculations. The data obtained is sent to the second layer, and the output is obtained. Synapses are essential to learning and getting a better understanding of the input.
It states that artificial intelligence has all the power to learn, which has turned magical. Now scientists do not have to create look-up tables for processing data. Now, just writing programs and training the computers has made our job very easy. Hence, today, computers can do image recognition, speech recognition, and more with the help of artificial intelligence within seconds.
Some prominent examples of artificial intelligence are:
Artificial intelligence in the self-driving car project is applied to identify the difference between a police vehicle and a car or bike with the help of image processing. Interestingly, the laser and ultrasonic sensors are combined to form three-dimensional models of the surrounding so that the car can navigate safely.
Also, the car is controlled automatically, and such automation is done with the help of artificial intelligence. A well-trained computer can identify the difference between a shark and a whale.
If a machine has calculating, computing power, and intelligence, a machine can do almost everything. Artificial intelligence will not only change our lives in small ways but will likely bring tremendous change to our lives. AI will give us unprecedented power and an opportunity to change.
Imagine ten years from now that we are autonomously developing a space station on Mars, your car is driving you to work, and you are talking to a robot. AI ensures a safe and fair trading environment, or scientists use AI to find mutations. And these are some of the possibilities!
The tech giants like Microsoft, Google, Facebook, and Apple are advancing at an incredible speed in improving artificial intelligence software. The power and the freedom of artificial intelligence that we have are empowering us to do more.