Artificial Intelligence (AI) is an area that is part of Computer Science and is responsible for developing machines that simulate human intelligence and behavior.
In practice, when you use a voice assistant on your cell phone or go through a chatbot service with a company, you are using Artificial Intelligence.
It is through AI and the technology involved in it that machines are able to interpret data and learn from it. And then use the learning for pre-determined tasks like analyzing reports or identifying trends.
The main objective of Artificial Intelligence is that machines are able to imitate humans in repetitive tasks such as analysis, reasoning, and decision making.
The history of Artificial Intelligence
Even before technology allowed AI to be created, people dreamed of using machines to perform various activities. In 1927, for example, the movie Metropolis already featured robots, computers, and programs that would be working with humans or seeking their destruction.
Furthermore, records show that in 1943 scientists Warren McCulloch and Walter Pitts published a paper talking about neural networks for the first time. This would be an artificial model to mimic the human nervous system.
Then, in 1950, Alan Turing was responsible for developing a way to assess whether a machine would be able to impersonate a human in written interaction.
Where did AI start from?
The ground zero of Artificial Intelligence was in 1956, at a conference called the Dartmouth Conference. It was at this event that minds that were thinking and studying about AI got together and started to get ideas off the ground.
As the prospects were encouraging, government and private representatives decided to invest in the area. Including DARPA (Defense Advanced Research Projects Agency) in the United States, which was where the internet was born.
For several years, between the 60s and 90s, Artificial Intelligence went through ups and downs. Since it was often not possible to put into practice what had been planned and expected.
It was in 1997 that a machine defeated a man playing chess for the first time. Professional chess player Garry Kasparov was defeated by an IBM machine, and that fact was known around the world.
Evolution of Artificial Intelligence over time
Although in the past the applications of AI were restricted, today this technology is capable of doing amazing things. In 2005 Boston Dynamics entered the Artificial Intelligence market with “BigDog”. This robot is able to move in terrains that are difficult for humans to access, and to this day the company works to evolve its products more and more.
At the same time, applications of AI in autonomous cars began, which still depend on the adaptation of highways and cities to become truly viable.
In addition to these applications, AI is present in people’s everyday lives due to cell phones, voice recognition systems, and virtual assistants.
These examples make it clear that AI is constantly evolving, and anyone who thinks it is just an interface for interacting with humans is wrong. In fact, Artificial Intelligence involves algorithms, codes, and complex structures to be created.
Types of Artificial Intelligence
Computer vision is a type of AI where computers and systems obtain information from digital images, videos, and other digital sources. Then, machines are able to put in practice predetermined actions.
While the concept of AI says that machines can think like humans, computer vision allows machines to see, observe and understand images.
One of the best uses of computer vision is in product inspection in industries. The machine is able to observe and analyze thousands of products per minute, identifying if there is a problem or defect that not even humans could detect.
Natural Language Processing
Another type of AI is natural language processing (NLP), which aims to provide the ability for computers to understand and create text.
Note that “understanding” a text includes: extracting information, analyzing feelings, recognizing the context, and performing analyzes (syntactic, lexical, morphological, and semantic).
A highlight of NLP applications is automatic text translation, which is considered by many to be the starting point for the use of machines to study natural languages.
Machine Learning is the application of AI so that computers can develop to the point of making decisions with minimal human participation. Learning from data and identifying patterns is indispensable for Machine Learning.
In practice, this area of AI is used to recommend movies on streaming platforms like Netflix. As the user makes their preferences and choices available, the machine is able to learn and reproduce these preferences through recommendations.
On the other hand, Deep Learning is another application of AI.
If you want to understand in more detail the differences between Machine Learning and Deep Learning, access our full article on the subject.
Deep Learning is actually part of Machine Learning, and this part of AI uses neural networks to perform speech recognition and simultaneous translations.
Examples of AI applications
Companies are constant sources of data that can be evaluated by Artificial Intelligence systems. Suppliers, customers, production processes, everything that happens in companies generates data that is rich in information for analysis.
AI can be used to enhance results, increase productivity, and optimize people’s time.
1. Chatbots for customer service
In order to serve more people in less time, companies use chatbots on their websites to optimize this service. When the robot is no longer able to assist the customer, the service switches to a human.
Thus, it is possible to automate activities such as updating records and consulting general information. And also reduce the number of calls and improve the response time to customers.
2. People management
The HR department of companies is also able to take advantage of AI. An example is the use of intelligent software to evaluate the performance of employees in certain tasks.
Thus, managers are able to make assertive decisions based on reliable data.
3. Anomalies prediction in the industry
Industries that have historical data can use Artificial Intelligence to predict anomalies in their production processes such as values of variables in industrial processes that are outside the process boundary.
In this way, AI works with time predictability, helping to manage expenses and optimizing any problems in the production process.
When managers can predict problems, it is possible to make the best decisions and have time to perform operational maneuvers.
In the steel industry, for example, it is possible to use AI to prevent risks in the coke oven.
Importance of AI and its increasing use
As it was possible to learn from this article, more and more Artificial Intelligence presents itself as an opportunity for industries and companies in general. To optimize processes and to make decision-making process easier are just some of the advantages of this technology.
To understand even more about AI, access the articles.