A lot of individuals have heard of artificial intelligence and machine learning. However, many remain unsure as to what exactly these concepts entail even though they have been part of our day to day life for a while now.
Artificial intelligence has been powering systems from those that appear seemingly mundane to life-changing ones so it is important to understand it fully so that we can make the most of the opportunities it presents.
Almost every industry nowadays is keen to incorporate AI for a variety of applications and cases. Some of the broad applications of AI include fraud detection, predictive analysis, enhanced customer support, process automation, and more.
Experts foresee AI as the future of technological and economic advancement. As such, the career opportunities available for AI engineers and programmers are slated to increase considerably in the next coming years.
But first, what exactly is artificial intelligence?
Artificial intelligence has been around for a while but it has only recently started garnering a lot of attention. Artificial intelligence is a technical discipline that carries out research as well as develops theories, systems, and technologies for simulating the growth and expansion of human intelligence.
Artificial intelligence research hopes to enable machines to perform complex tasks that require human intelligence. The hope is that machines can replace human labor and thinking to solve complicated tasks.
If you are an individual that has no prior knowledge about AI but is very much curious about the field, there are some basic foundational concepts that you should be aware of. These concepts include:
People often use the terms machine learning and artificial intelligence interchangeably. However, as some of the best artificial intelligence books point out that the two are considerably different. Machine learning is a core concept in artificial intelligence.
Human beings have various methods of learning. We have accumulated knowledge for centuries from our ancestors but we also create new knowledge by inference. The purpose of machine learning is to give machines such ability.
Machine learning, therefore, provides systems and machines with the ability to automatically learn and improve from experience rather than being explicitly programmed. Basically, AI helps machines act less like machines and more like humans. Thanks to machine learning, tasks that were only reserved for people will now easily be carried out by machines.
At the highest level, machine learning is the process through which a computer system is taught how to make accurate predictions whenever it is fed data. The predictions made could vary from identifying whether a fruit in a photograph is an apple or orange or spotting whether pedestrians are standing in front of a self-driving car.
Is it possible to make a machine learn more than one particular task? What if you want to make a photo recognition machine use what it has learned from analyzing photos to instead analyze different sets of data?
For a machine to be able to do much more than it was designed to do, a computer scientist must develop general-purpose learning algorithms that will then help the machine learn more than it was created for.
For deep learning to occur, structured machine learning algorithms in the shape of artificial neural networks must be utilized. The algorithms allow the machine to learn by itself and be able to create its own standards and restrictions for making and executing decisions. Deep learning, therefore, does not require human intervention.
Deep learning carries out its processing via artificial neural networks. Neural networks imitate neurons or human brain cells. Neural net models make use of math and computer science principles to mimic the behavior of the human brain so that general learning can take place.
An artificial neural network is created to simulate or copy the processes of densely interconnected brain cells. However, instead of the cells occurring naturally from biology like in humans, artificial neurons or nodes are created from code.
Artificial neural networks are designed to imitate human behavior as much as possible so that data can be computed in various layers of interconnected neurons. Artificial neurons transform and communicate information between each other, which is essentially how deep learning occurs.
Neural networks are available in 3 primary layers; an input layer, a hidden layer, and an output layer. Each of these layers contains thousands to millions of nodes. Information and knowledge are typically fed through the input layer.
When all the three primary concepts of AI- machine learning, deep learning, and neural networks are combined, it allows hardware and software robots to act and think dynamically, outside the confines of code. Once you understand how the 3 concepts work, then you will be able to explore more advanced AI topics such as artificial general intelligence, superintelligence as well as ethics in Artificial Intelligence.
So far, AI is still at the stages of weak intelligence, meaning that machines do not have autonomous consciousness yet. As the field continues to advance and we make huge steps in technological innovations, strong artificial intelligence will be the norm. this means that machines will be so intelligent that they will surpass human beings in the future.
Artificial intelligence has been progressing at an alarming rate. Efforts to advance the field over the past 2 decades has paved the way for some truly fascinating advancements. These range from medical research, big data and autonomous vehicles are just some of the few well-known applications that have emerged from AI innovation.
To understand some of the more complex concepts of AI such as data mining, driving software and language processing, it is first essential that you understand the 3 primary concepts of AI, that is, deep learning, machine learning and neural networks. It is these basic concepts that make it possible for machines to act and think as dynamically as they do as a result of AI.
AI is a broad but enormously fascinating topic. Hopefully, this brief overview of some of the basic concepts will give you a better understanding of what AI entails. Once you understand the basics, you will then be able to comfortably and confidently explore some of the more advanced topics such as intelligence and superintelligence.