Artificial intelligence

The first step in advanced artificial intelligence, the debate on artificial neural networks arose in the 1940s, among scientists at the University of Illinois, in an effort to associate human nerve cells with electronic processes.

It was in the mid-1960s, with the advent of the first computers, that the study of this relationship between the functioning of neurons, and the modeling of electrical systems, allowed the creation of simulations of neural networks.

With the subject on the rise, computing and artificial intelligence were understood as the same thing. For the first time, we are using machines, basically for calculating, better than the human brain, with greater processing capacity.

However, the beginning of computing soon presented its limitations, with low hardware technology and little practical application.

It was in the 1980s that the artificial intelligence agenda gained momentum again. We call this moment of machine learning technology, until about the year 2010.

Machine learning is nothing more than machine learning, that is, the technology that automates analytical processes to create algorithms, using data for its “learning”, a kind of constant training.

And technology has advanced beyond machine learning.

Today, we come to deep learning, a step further in machine learning. More than simple learning through algorithms, deep learning allows the formation of neural networks capable of simulating actions in the human brain itself.

Thus, it is possible to train the technology for more refined actions, such as classifying images, detecting objects, making predictions and describing content in detail. Technologies based on deep learning are fed with large volumes of data and rely on high computational power.

We can cite as examples of deep learning, in our daily lives, the Google Assistant, the virtual assistant Alexa, Siri and ChatGPT.

Artificial intelligence automates repetitive learning and discovery. Unlike simple automation, focused on manual tasks, artificial intelligence is focused on frequent and computerized tasks, dealing with more complex systems. Lets look at some benefits.

The most common artificial intelligence, in our daily lives, is not sold individually. That is, the technology itself is not used “alone”, but combined with other types of products, such as robots in industry, smart appliances, cell phones and devices that combine a variety of data, among others.

The tendency is for technologies like this to be inserted even more, little by little, in other situations for the residential and security environment, for example.

Artificial intelligence has the ability to find structures in data, making it a kind of “classifier”.

That is, the algorithm in these technologies manages to teach itself a classification, for example, the products advertised online for each type of consumer. And the more data they receive, the more accurate their indications become.

The new generations of artificial intelligence use more and more data to improve their ability to read systems. Combined with the computational capacity we have today, AI is becoming increasingly accurate and has enormous potential for all areas of society.

By relying on neural networks for machine learning, AI today has a previously impossible capacity for interactions. For example, tools like ChatGPT, Google, or Alexa interactions, which are based on deep learning, tend to increase in accuracy the more they are used.

It is important to note that everyday activities that seem basic, such as a simple Google search, are just a tip of the enormous potential that AI has for society. And new ways of using this type of technology appear all the time.

And your company, is it already prepared for the latest technology?