What is Artificial Intelligence – Artificial Intelligence emerged in the 1950s and is the ability of machines to perform certain operations as well as humans. While weak artificial intelligences only perform what you have programmed, strong artificial intelligences are systems that can improve what you have programmed by making algorithmic calculations and learn from mistakes.
Artificial intelligence has recently started to be discussed both in the world and in our country. Some predict that artificial intelligence will reduce manpower, thus causing unemployment, while others predict it will create great opportunities. So, what is this artificial intelligence?
What is Artificial Intelligence
Artificial intelligence, as we can express it as systems or machines that imitate human intelligence and can continuously improve itself according to the information they collect, in order to fulfill the given tasks, in other words, Artificial intelligence; We can describe it as a set of software and hardware systems with many abilities such as exhibiting human-like behaviors, numerical reasoning, movement, speech and sound perception.
When asked any question to the artificial intelligence, it chooses and presents the most rational one among the answers given for the same question given or defined before. For this reason, each time the same question asked comes up again, artificial intelligence filters the answers to the same question and presents the most rational one.
It would be wrong to consider artificial intelligence under a single heading. Concepts such as machine learning and Deep learning are inclusive terms that make up artificial intelligence.
To understand the difference between the terms Artificial intelligence, Machine learning and Deep learning, it is useful to review the chronological order below.
What is Machine Learning?
Machine learning emerged in the 1980s and started to become more popular with the use of data mining. They are self-training systems that can make better determinations than you, reveal what you have not programmed, by making simulations with the data and parameters you have presented.
Machine learning is algorithms that enable the machine to derive logical and rational results from the data provided. For example; An algorithm is written about the shopping receipt data of customers in a store. This algorithm; They detect that sales are increased when the materials consumed together are kept in the aisles close to each other, and the arrangement is adjusted accordingly. With the arrangement made in this way, the customer who buys a good also buys the other related good next to him, and the sales of this good are increased. In this example, we have covered machine learning in its simplest form. Machine learning offers us information that will push the limits of the mind in today’s technologies.
What is Deep Learning?
Deep learning is a system that started to be used in the 2010s, makes calculations used in machine learning in many layers, not in a single layer with a sea of big data, at once, discovers even the parameters that you need to define in machine learning, and maybe can make evaluations with better parameters.
Deep learning is a technology that can be seen from the chronological order, which is a sub-branch of both Artificial intelligence and Machine learning. What is this Deep learning? What does it do?
Deep learning and Machine learning are very similar structures. Deep learning works like neurons in our brain. Let’s reveal the concept of Deep learning with the example of grapes.
While we introduce the features of Grape in machine learning, it creates its own rules in deep learning; It can distinguish which is banana and which is grape by its own processes.
The more data there is, the better artificial intelligence features will be revealed. Things will get more complex, as they get more complex there will be shifts from artificial intelligence to machine learning. As it gets more complex, the transitions from machine learning to deep learning will begin. The more data you have, the better your system will run.
While machine learning processes in a single layer, deep learning processes in many layers simultaneously.
E.g; we need to separate a picture of a banana and a picture of an orange. In machine learning, we were trying to introduce the experience of human beings to the machine through parameters. Well, if it’s orange, it’s probably orange, and if it’s yellow, it’s like a banana. If it’s round it’s probably an orange, if it’s an arc it’s probably a banana, etc. We had to define many parameters.
However, deep learning can learn this difference on its own. By only showing the orange and banana pictures to the deep learning system, he creates his own rules and realizes that color and shape are the main distinguishing features in order to reveal the differences. Thus, without the need for basic human abilities, it can perform its operations by creating its own decomposing abilities.