There are many market trends that, when least expected, become reality. In recent times, technological development has guided the improvement of several corporate processes. Cloud technology is here to prove this. In this context, every manager has the duty to know what machine learning is. More than ever, they must know why this concept has become so relevant in the current scenario.
You may have noticed that the dream world of science fiction movies is no longer so surreal. This is partly due to the advancement of AI (artificial intelligence), which derives from the quantity and variation of complex systems.
If you pay close attention, you will see that AI is spreading across many areas. While it is present in everyday activities, it is also vital for the industrial sector that uses cutting-edge technology .
What does machine learning have to do with all this? Here’s what you’ll find out! Without a doubt, covering the topic in one post would be too ambitious. Instead, we’ll cover the concept in its main nuances.
So, if you want to find out what machine learning is and how the concept is linked to the future of your company, you’ve come to the right place! Enjoy your reading!
What is machine learning and how did this concept come about?
It was only in 1950 that the first attempts to slightly improve the performance of these machines began. At the end of the same decade, Arthur Samuel, an IBM programmer, developed a system that went beyond performing calculations.
The machine used by the system began to deepen its relationship with the commands it received. This was proven by a simple game of checkers. When he noticed that the system had developed a strategy to defeat him, Samuel defined it as learning. Since it involved a machine, the expression machine learning emerged .
Therefore, if we could summarize what machine learning is, we could say that it is the self-learning of machines. There is an important detail in all this: when we talk about self-learning, we are referring to the absence of specific programming for it.
Machine learning VS artificial intelligence
By now, you may have already deduced that AI is contemporary with the arrival of so-called machine learning. Yes, artificial intelligence was coined in 1956. Let’s look at the most relevant aspects of each concept:
Artificial intelligence
The AI boom is, in fact, very recent. To be more precise, it was only in 2012 that this type of intelligence demonstrated some of its potential. The accelerated expansion of the accumulation of data dumped onto the internet in recent years has led to significant investment in GPUs. The latest generation of graphics processing units have been crucial in enabling images to be transformed into video instantly.
Basically, AI involves the combination of algorithms and other elements capable of creating an environment that is favorable to the development of an autonomous system. An obvious example is the self-driving car itself. However, note that certain mechanisms, such as Google Voice, also exhibit an infrastructure linked to AI.
Machine learning
In fact, machine learning is an item integrated into artificial intelligence, which is broader. In practice, machine learning is a system developed with the aim of providing extremely better and faster results.
This happens because machine learning gives the machine the ability to analyze a large volume of data in a fraction of a second. Note that no previous processes are lost. Instead, the machine prepares the next actions based on the quality of the previous results. Therefore, it learns. It is no wonder that one of the characteristics of machine learning is prediction.
Machine learning VS deep learning
The deep learning method is named as such because of its operating method, which is inspired by human neural networks. It is, therefore, a model of artificial neural networks. This means that the system is almost as complex and perfect as the functioning of the human brain .
The progress made in deep learning is already visible to any internet user. Since 2016, Google has been using this machine learning method in its automatic translation systems. This explains why the quality of these translations has improved significantly since that time.
How important is it for the future of companies?
There is no doubt that the system behind deep learning is even more daring than its predecessors. By using the brain as a reference, developers aim to make systems even more intelligent and effective.
The possibilities for optimization in the most varied sectors of the economy are immeasurable. In industry, the forecast is for an even more detailed improvement of production processes. Thus, an increase in manufacturing time and in the quality of goods is expected.
In laboratories, monitoring mechanisms must become increasingly accurate. Therefore, the risk of errors related to the concentration of substances tends to be reduced as much as possible. Added to this is the ability to issue alerts earlier in the event of problems.
You don’t need to own a multinational company to experience machine learning in action. Just think of the automatic text corrections on messaging apps. Even the route recommendation system used by Waze, for example, is based on machine learning.
You can also partner with startups dedicated to developing systems based on machine learning. How about having a system capable of making accurate purchase suggestions to customers? With such technology, almost anything is possible.
