All You Know About Artificial Intelligence , Machine Learning And Deep Learning
In this article, we’re going to discuss on Artificial Intelligence, Machine Learning and Deep learning. Organizations see Artificial Intelligence as a tool to differentiate themselves from the competition, obtain greater knowledge of the client, improve the efficiency of workers and promote innovation , according to one of the latest studies prepared by IDC . Furthermore, they forecast that investment in AI solutions will continue to grow at a compound annual growth rate of 24.5% through 2025.
The consultancy affirms that “the acceleration of the adoption of AI and the proliferation of more intelligent and intuitive algorithms of Machine and Deep Learning will propitiate the creation of new industries and commercial segments and, in general, will generate new opportunities for business monetization”.
Therefore, taking into account the crucial role that Artificial Intelligence plays today, and that will increase in the coming years, as well as its various applications in the business field, below we will show what are the differences between AI, Machine Learning and Deep Learning.
Who Is Who?
Before detailing their differences, it is convenient to briefly define each of these terms in order to better understand their enormous capabilities.
Artificial Intelligence : it is a set of technologies that through computer systems simulate the processing of the human brain. The combination of these technologies allows processes to be executed or complex problems to be solved autonomously thanks to learning, reasoning and self-correction.
Machine Learning : also known as machine learning, it is a discipline of Artificial Intelligence and, through it, computers learn to identify patterns without having to be previously programmed.
Deep Learning : is a Machine Learning technique with which computers not only identify and learn concepts, but also understand complex contexts and environments due to the large number of layers of learning it has. With Deep Learning, and especially due to the set of algorithms that mimic the neural networks of a human brain, the machine reasons and draws its own conclusions, learning by itself.
What Is The Difference Between Them?
After knowing the meaning of each of these technologies or disciplines , we now delve into the differences between them.
As we have already seen, Artificial Intelligence is the main technology from which Machine Learning and Deep Learning emanate, which have evolved and endowed machines with greater autonomy.
At first, the AI only solved a problem by obeying the rules by which it was programmed. That is, before the problem A had to do B, and the machine was limited to fulfilling those orders.
However, with the arrival of Machine Learning, machines began to learn what they had to do at all times and solve certain situations on their own.
This is achieved thanks to the work of the programmers, in charge of training the robots by exposing them to a large amount of data that they have to process, analyze and learn. In this way, computers have a better understanding of the situations they may face in order to choose the best solution or response.
Finally, Deep Learning goes beyond Machine Learning. This is where Artificial Neural Networks (ANNs) come into play, which mimic neurons in the human brain. This technology works by layers of learning or knowledge, so the more layers the machine has, the greater its degree of learning and processing.
Thanks to this, Deep Learning or deep learning is used in tools or platforms that require a more complex technology, capable of knowing the context or everything that surrounds it to make the best decisions, as is the case, for example, of autonomous vehicles.