Do you know what Deep Learning is? Although the terms are sometimes unclear, in many cases, they are essential for the company to continue innovating and growing in the market.
Those who like futuristic movies, for example, may be scared by the various 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 what applications are already available on the market. Good reading!
What Is Deep Learning?
You must have seen movies where robots can think and act independently, correct? Deep Learning, better known as deep Learning, is the closest thing to this, as it can adapt to changes and make generalizations when it needs to work with partial information.
In an agile way, Deep Learning can assess a goal, correctly understanding the information to adapt to the main variants. For it to evolve, it was based on Machine Learning, inheriting the main characteristics of machine learning and teaching it new skills.
It is expected that machines can learn new skills and knowledge so as not to lose space in the market — which is also the case with today’s professionals.
What Are The Differences To Machine Learning?
In summary, Machine Learning is one of the main developments of Artificial Intelligence that gives the computer the ability to learn. More than that: just like the human mind, the machine can learn new skills when exposed to a set of different data and information.
An excellent example of this is the news feed of the leading social networks. It tries to understand your preferences when displaying content, classifying it according to what it believes is most relevant to you. As people’s preferences change, they must 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 since the processes are intuitive.
How Does It Work In Practice?
Deep Learning is designed to analyze data continuously, concluding in a human-like way. For this capability, applications use layered structures called artificial neural networks.
As you can assume, the model for this is the neural network present in the human brain, making the possibility of learning more efficient and capable than what is found in Machine Learning.
Initially, it may be challenging to configure it to prevent the system from drawing hasty or incorrect conclusions, as happens in some cases of AI. Therefore, a lot of training may be required. Afterward, however, everyone involved marvels at what a brilliant structure looks like.
To understand better, you can think of the application created by Google, Alpha Go. It is a program with a neural network and has masterfully learned to play a board game called Go, well known for requiring players to have intuition and intelligence.
After learning to play with professionals, Google’s deep Learning achieved results never before obtained with an artificial intelligence application since it did not need to be trained to know how it should act in a specific move, as happens in the Machine Learning model.
The result was that AlphaGo was able to defeat many of the world’s great players, including the number 1 player. He understood the game’s rules and the more complex techniques and abstract aspects that could help him win. In other words, he became one of the great players in the world. With that, it was retired, and the results were available to Google for other applications.
What Are Your Primary Services?
See which are the primary services that use Deep Learning in the market.
Alexa, Cortana, and Siri are examples of virtual assistants that use deep Learning to understand how people use language and interact with them in the most natural way possible.
Chatbots And Service Bots
Chances are you’ve already needed support and been greeted by a chatbot or service bot. They can learn intelligently with both text and audio questions. With deep Learning, the number of questions that can be answered is constantly increasing, improving overall user satisfaction.
Facial recognition can be used for various 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 so, it will be necessary to learn to identify confidently, even when the person has grown or changed their look drastically.
How Can Deep Learning Optimize IT Processes?
You’ve seen how powerful the possibilities are, haven’t you? This feature can also make business processes more efficient and faster. Over time, it can be guaranteed that the error rate will be lower as the systems stay energized and focused.
In addition, they can learn over time which is the best way to perform the service. In this way, all companies can gain productivity and even reduce costs.
Also Read: How To Choose A Business Management System