Artificial Intelligence has different meanings for different people. A broad definition, based on what the fathers of the concept Marvin Minsky and John McCarthy said, is that artificial intelligence is all about machines performing the tasks that traditionally needed human intelligence. This is a comprehensive as well as simpler way of making sense of what AI could be. This definition, however, can convolute things if we use it to decide which technology is AI-oriented and which is not.
Before Minsky and McCarthy, there was another man who was the first to ask the consequential question – “can machines think?” It was Mathematician Alan Turing, after changing the direction of World War II, who wrote a significant paper on “Computing Machinery and Intelligence” in 1950 that later became the fundamental vision for artificial intelligence as a technology concept.
Since Turing asked the question, another branch of computer engineering science came into existence that solely worked to answer what Turning asked through every new breakthrough. With artificial intelligence, scientists asked themselves and answered whether the next machine they are working on is capable of thinking or not. Artificial intelligence since then has become the science that makes machines think and our world easier for humans in the process.
There are many modern definitions that throw more light into the concept and how it is actually applied in use. An artificial intelligence researcher at Google who created the machine-learning software library Keras, Francois Chollet also gave a working definition of the concept. Chollet said, “Intelligence is the efficiency with which you acquire new skills at tasks you didn’t previously prepare for. Intelligence is not a skill itself; it’s not what you can do; it’s how well and how efficiently you can learn new things.”
One simpler way of understanding artificial intelligence is to define it by its capabilities. Any technology that has some sort of human behaviour linked to its core functionality can be called artificial intelligence oriented. So, if a machine can plan, learn, reason, solve problems, represent knowledge, give perception, create motion, or manipulate the third function or intelligence or creativity is what artificial intelligence means.
What is important to understand here is that artificial intelligence is no longer the dream of the future. It is very well present in our lives and has been for some time. Artificial intelligence is one ubiquitous energy today that empowers every active part of our lives. From the fan on your ceiling to the car you drive, every single consumer product these days has artificial intelligence oriented features in one way or another. Whether is the smart products engulfing our everyday lives or the prospects of having a self-driving parked outside our homes, artificial intelligence is everywhere now. As a result, most consumer product manufacturers or most small or medium tech companies have now a dedicated research department related to artificial intelligence and are investing heavily in the integration of the technology into their products. To further understand, let’s get into how artificial intelligence works.
An artificial system has multiple components that can be viewed as sub-fields of a science that works to bring AI to life. These sub-fields are heavily utilised in realising any type of artificial intelligence related product or service or function. The sub-fields include Machine Learning, Deep Learning, Neural Networks, Cognitive Computing, Natural Language Processing, and Computer Vision amongst others. Let’s understand each of these sub-fields in a little bit detail.
Machine Learning – Machine Learning enables computers, programs or computer applications to learn a system automatically without it being programmed to do this specifically. Through Machine Learning, these computers or programs also better their functionalities or develop a better understanding completely based on their experience, a unique similarity to human intelligence.
Deep Learning – This allows artificial intelligence to process data and further learn or improve accordingly. Artificial neural networks are used which in return mimic biological neural networks to process information. They do many tasks with the information such as connecting dots in the data or finding out inferences.
Neural Networks – It analyzes data sets repeatedly to come up with associations and interpretations. As the same suggests, neural networks mimic the function of human brain neuron networks and in the process allow artificial intelligence to study large data sets and get an answer to specific queries.
Cognitive Computing – Cognitive computing is yet another vital component of artificial intelligence systems that imitate the interactions between humans and machines. This function lets computer models work like a human brain would work. It is mainly used for complex tasks including functions such as text analysis, speech or image analysis.
Natural Language Processing – Artificial intelligence does one thing like no other technology and that is it allows the system to perform like humans. It allows computers or programs to recognize, analyze, interpret, and truly understand human language in the process, which can be ground breaking in coming times. Natural Language Processing is a significant part of artificial intelligence oriented programs as an AI-driven system interacts with humans based on this technology.
Computer Vision – Artificial intelligence reviews and interprets the content presented in front of it whether it is an image or text. Computer vision is how pattern recognition and deep learning work. Computer Vision allows artificial intelligence systems to identify components of the visual data presented in front of it. This includes captchas that are mostly found across the web. Most of us have faced this program online where humans are asked to identify cars, crosswalks, bicycles, and mountains in order to recognize and proceed further with the interaction with the system.
In simple words, artificial intelligence works by allowing machines, systems or computer applications to mimic human intelligence. It mimics how to read, learn, and learn from experience like humans through iterative processing and various types of algorithmic training.
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