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What is Artificial Intelligence? How do AI work, its Types, and its Future of?

Introduction to Artificial Intelligence

The intelligence demonstrated by machines is known as Artificial Intelligence. Artificial Intelligence has grown to be very popular in today’s world. It is the simulation of natural intelligence in machines that are programmed to learn and mimic the actions of humans. These machines are able to learn with experience and perform human-like tasks. As technologies such as AI continue to grow, they will have a great impact on our quality of life. It’s but natural that everyone today wants to connect with AI technology somehow, may it be as an end-user or pursuing a career in Artificial Intelligence.


There are many technologies and disciplines that involve Artificial Intelligence, which has their own branches of mathematical and engineering study. Let’s take a look at the most relevant technologies, starting with recognition systems through to machine learning systems.

Automatic speech recognition

Automatic speech recognition is a discipline belonging to acoustics that recognizes phonemes in a voice signal. The voice recognition systems process the signal collected by a microphone to identify the words pronounced by the user.

Natural language processing NLP

While speech recognition focuses on the pure conversion of voice to text, Natural Language Processing NLP is a discipline that is more closely linked to the field of linguistics, and its objective is to understand what the user means when making a certain command, question, or statement (either written or vocal) and what he expects to achieve. In addition, it analyzes the mood to find subjective patterns. In short, it is the field that helps communication (mainly sound and written) between machines and humans.

Visual Recognition

Visual recognition is the discipline based on processing an image or video signal, with the aim of recognizing patterns, shapes, and in the best cases, accurately identifying the different elements in an image.

Text Recognition

Text recognition could be considered a part of visual recognition, as its main objective is to recognize and identify text in image formats. It is common to use OCR (Optical Character Recognition) tools for this work.

Big data

Without going into technicalities, Big Data can be considered as a large volume of data. Big Data alone is not a technology but having a huge amount of data (preferably structured) available is vital for achieving objectives both in Business Intelligence analysis and in the application of certain Machine Learning algorithms.

Expert systems

Expert systems are those which contain all possible human knowledge about a particular topic. A classic example is the systems that play chess, which use a whole collection of movements and strategies, that have been input in their memory, to determine the best move (usually based on decision trees).


Robotics (either mechanical or robotic software, such as RPA) covers a wide range of devices. Whenever a system or robot shows signs of intelligence, for example, being able to make decisions, however basic they may be, we can be talking about Artificial Intelligence. Remember that AI does not have to be especially sophisticated, it exists at all levels, even the most basic ones, and it must be differentiated from the ability to learn from machines; that is, Machine Learning.

Machine Learning

Machine Learning is the discipline, within Artificial Intelligence, that tries to get a system to learn and relate information the way a person would. To do this, it uses algorithms that are able to detect patterns in previous data, being able to create future predictions, as well as new trends such as Deep Learning and its neural network algorithms.

Deep Learning

Deep Learning is a subdiscipline of Machine Learning. It is a learning system that is inspired by the functioning of the neural networks of the human brain to process information, with a very complex mathematical basis. Although it does rely on experience (whether previous data, generated by the environment or self-generated), it does not start from strict indications that determine what is correct and what is not, so the system can determine conclusions on its own.

Cognitive Intelligence

Cognitive Intelligence is a combination of the previously mentioned technologies with the aim of creating artificial intelligence services capable of having human understanding. It is the union of visual recognition, sound, reading comprehension, NLP, and Machine Learning to create systems capable of understanding information related to human interaction and responding accordingly.

How does artificial intelligence differ from human intelligence?

So how is AI different from human intelligence? Artificial intelligence and the algorithms that make this intelligence run are designed by humans, and while the computer can learn and adapt or grow from its surroundings, at the end of the day it was created by humans. Human intelligence has a far greater capacity for multitasking, memories, social interactions, and self-awareness. Intelligence that is artificial doesn’t have an I.Q. making it very different from humans and human intelligence. There are so many facets of thought and decision-making that artificial intelligence simply can’t master—computing feelings just isn’t something that we can train a machine to do, no matter how smart it is. You can’t automate multitasking or create autonomous relationships. Cognitive learning and machine learning will always be unique and separate from each other. While AI applications can run quickly, and be more objective and accurate, its capability stops at being able to replicate human intelligence. Human thought encompasses so much more than a machine simply can’t be taught, no matter how intelligent it is or what formulas you use.

How does AI work?

While it’s one thing to know what AI is, it’s another to understand the underlying functions. Artificial intelligence operates by processing data through advanced algorithms. It combs large data sets with its algorithms, learning from the patterns or features in the data. There are many theories and subfields in AI systems including:

Machine learning. Machine learning uses neural networks to find hidden insights from data, without being programmed for what to look for or what to conclude. Machine learning is a common way for programs to find patterns and increase their intelligence over time.

Deep learning. Deep learning utilizes huge neural networks with many layers, taking advantage of its size to process huge amounts of data with complex patterns. Deep learning is an element of machine learning, just with larger data sets and more layers.

Cognitive computing. Cognitive computing has a goal for a human-like interaction with machines. Think robots that can see and hear, and then respond as a human would.

Computer vision. In AI, computer vision utilizes pattern recognition and deep learning to understand a picture or video. This means the machine can look around and take pictures or videos in real-time, and interpret the surroundings.

The overall goal of AI is to make software that can learn about input, and explain a result with its output. Artificial intelligence gives human-like interactions, but won’t be replacing humans anytime soon.

How is AI used?

Artificial intelligence is being used in hundreds of ways all around us. It has changed our world and made our lives more convenient and interesting. Some of the many uses of AI you may know to include:

Voice recognition. Most people know to call out for Siri when they need directions, or to ask their smart home Alexa to set a timer. This technology is a form of artificial intelligence. Machine learning helps Siri, Alexa, and other voice recognition devices learn about you and your preferences, helping it know how to help you. These tools also utilize artificial intelligence to pull in answers to your questions or perform the tasks you ask.

Self-driving cars. Machine learning and visual recognition are used in autonomous vehicles to help the car understand its surroundings and be able to react accordingly. Facial recognition and biometric systems help self-driving cars recognize people and keep them safe. These cars can learn and adapt to traffic patterns, signs, and more.

Chatbots. Many companies are utilizing artificial intelligence to strengthen their customer service teams. Chatbots can interact with customers and answer generic questions without needing to use a real human’s time. They can learn and adapt to certain responses, get more information to help them produce a different output, and more. A certain word can trigger them to put out a certain definition as a response. This expert system can give a human level of interaction to customers.

Online shopping. Online shopping systems utilize algorithms to learn more about your preferences and predict what you’ll want to shop for. They can then put those items right in front of you, helping them grab your attention quickly. Amazon and other retailers are constantly working their algorithms to learn more about you and what you might buy.

Streaming services. When you sit down to watch your favorite TV show or listen to your favorite music, you may get other suggestions that seem interesting to you. That’s artificial intelligence at work! It learns about your preferences and uses algorithms to process all the TV shows, movies, or music it has, and finds patterns to give you suggestions.

Healthcare technology. AI is playing a huge role in healthcare technology as new tools to diagnose, develop medicine, monitor patients, and more are all being utilized. The technology can learn and develop as it is used, learn more about the patient or the medicine, and adapt to get better and improve as time goes on.

Factory and warehouse systems. Shipping and retail industries will never be the same thanks to AI-related software. Systems that automate the entire shipping process and learn as they go are making things work more quickly and more efficiently. These entire systems are transforming how warehouses and factories run, making them more safe and productive.

Educational tools. Things like plagiarism checkers and citation finders can help educators and students utilize artificial intelligence to enhance papers and research. The artificial intelligence systems can read the words used, and use their databases to research everything they know in the blink of an eye. It allows them to check spelling, grammar, for plagiarized content, and more.

There are many other uses of AI all around us every day, technology is advancing at a rapid pace and is continually changing how we live.

What is the future of AI?

AI systems are already impacting how we live, and the door to the future is wide open for how it will impact us in the future. AI-driven technology will likely continue to improve efficiency and productivity and expand into even more industries over time. Experts say there will likely be more discussions on privacy, security, and continued software development to help keep people and businesses safe as AI advances.

While many people are worried that robots will end up taking their jobs, the truth is that there are many fields that are fairly safe from automation. Fields like IT will continue to be needed to adopt the new technologies and security systems that make AI run. Healthcare professionals and teachers won’t be able to be replaced by robots—the work they do directly with patients and children is something that can’t be replicated. Similarly in business, some processes can be automated, but human instinct, decision making, and relationships will always be vital for the future.

Artificial intelligence is transforming the way the world runs and will continue to do so as time marches on. Now is an ideal time to get involved and get a degree in IT that can help propel you to an exciting AI career. You can be a part of the world-changing revolution that is artificial intelligence.


In short, there have been extraordinary advances in recent years in the ability of AI systems to incorporate intentionality, intelligence, and adaptability in their algorithms. Rather than being mechanistic or deterministic in how the machines operate, AI software learns as it goes along and incorporates real-world experience in its decision-making. In this way, it enhances human performance and augments people’s capabilities.

Of course, these advances also make people nervous about doomsday scenarios sensationalized by movie-makers. Situations where AI-powered robots take over from humans or weaken basic values frighten people and lead them to wonder whether AI is making a useful contribution or runs the risk of endangering the essence of humanity.