What is Deep Learning and how does it improve company processes?

Do you know what Deep Learning is? Although the terms are not always very clear, in several cases they are essential for the company to continue innovating and growing in the market.

Those who like futuristic movies, for example, may be startled by the many possibilities that technology already provides today for people and companies, helping both to increase productivity and reduce costs.

In this text, you will understand what Deep Learning is, how it works and which applications are already available in the market. Enjoy your reading!

What is Deep Learning?

You may have seen movies where robots are able to think and act on their own, right? Deep Learning is the closest thing to this, as it can adapt to changes and make generalisations when it needs to work with partial information.

That is, in an agile way, Deep Learning can make evaluations of a goal, understanding correctly the information to be able to adapt to the main variants. In order for it to evolve, it was based on Machine Learning, inheriting the main characteristics of machine learning and teaching it new skills.

Machines are expected to have the ability to learn new skills and knowledge in order not to lose market share - which is also the case for today's professionals.

What are the differences for Machine Learning?

In a nutshell, Machine Learning is one of the main developments of Artificial Intelligence that gives computers the ability to learn. More than that: just like the human mind, the machine is able to learn new skills when it is exposed to a different set of data and information.

A good example of this is the news feed of the main social networks. It tries to understand what your preferences are when it comes to displaying content, ranking it according to what it believes is most relevant to you. As people's preferences change, it also needs to adapt to new tastes or desires.

Therefore, the main elements of Machine Learning are predictive and statistical analysis. With this, it is possible to find patterns and gain insights from the observed data.

Differently, Deep Learning can be understood as an even lower part of the process, since in the case of deep learning there is no need for manual intervention, as the processes are intuitive.

How does it work in practice?

Deep learning is designed to do continuous analysis of data, drawing conclusions in a human-like manner. To have this capability, applications use layered structures, called artificial neural networks.

As you might guess, the model for this is the very neural network present in the human brain, making the possibility of learning more efficient and capable than is found in Machine Learning.

Initially, it may not be easy to set it up to the point of preventing the system from drawing hasty or incorrect conclusions, as happens in some AI cases. Therefore, a lot of training may be required. Afterwards, however, everyone involved is amazed at how they are faced with a truly intelligent framework.

To get a better understanding, you can think about the application created by Google, Alpha Go. It is a program that has its own neural network and has learnt to play a board game called Go, which is well known for demanding intuition and intelligence from the players.

After learning to play with professionals, Google's deep learning achieved results never before achieved with an artificial intelligence application, as it did not need to be trained to know how it should act on a specific move, as happens in the Machine Learning model.

The result was that Alpha Go managed to defeat several of the great players from around the world, including the one considered to be number 1. He understood not only the rules of the game, but also the more complex techniques and the more abstract aspects that could help him achieve victory. In other words, he became one of the world's great players. With this, he was retired, and the results became available to Google for other applications.

What are your main services?

See which are the main services using Deep Learning in the market.

Virtual Assistants

Alexa, Cortana and Siri are examples of virtual assistants that use deep learning to understand how people use language and be able to interact with them in the most natural way possible.

Chatbots and service bots

You've probably needed service and been greeted by a chatbot or service bot. They are able to learn intelligently with both text and audio questions. With deep learning, the amount of questions that can be answered is always increasing, improving overall user satisfaction.

Facial recognition

Facial recognition can be used for many purposes, such as recognizing faces in photos on social networks and even facilitating payment methods (in the future, it will be possible to make payments only with faces). To do this, it will be necessary to learn how to reliably identify, even when the person has grown or changed their look drastically.

How can Deep Learning optimise IT processes?

You have seen how powerful the possibilities are, haven't you? This feature can also be used to make business processes more efficient and faster. Over time, you can guarantee that the error rate will be lower, as systems don't get tired or distracted.

In addition, they can learn over time what is the best way to perform the service. In this way, all companies can have some kind of productivity gain and even a reduction in costs.

Now that you know what deep learning is, you can be aware of the innovations that will happen in the future. The trend is for companies to become more and more automated and intelligent, which will make competition in the market even tougher. What is the limit of technology? We don't know yet. So you shouldn't limit your company either. So, look for the best solutions.

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