What is Artificial Intelligence?

What is Artificial Intelligence?

Artificial intelligence or AI is the simulation of human intelligence in machines created to think like humans and mimic their actions. Artificial intelligence can learn, make decisions and solve problems like a human. AI works by incorporating large data sets with intelligent algorithms to learn from patterns in the data they analyze. Each time an AI system runs, it measures and tests its performance. Therefore, as AI runs more, it becomes smarter, has fewer errors and becomes faster.

The 4 types of Artificial Intelligence

There are 4 types of artificial intelligence which are reactive machines, limited memory, theory of mind and self-aware. Each of these has its own set of qualities that classify these machines in each category. The reactive machines are the simplest and the self-aware category is the most complex artificial intelligence.

Máquinas Reactivas

Reactive machines are the most basic of the AI categories. Reactive machines do not have the ability to form memories or use past experiences to decide on current decisions. This means that they can only react to present scenarios and cannot recall past data or scenarios to make decisions.

Deep Blue is an example of a reactive machine. Deep Blue was a form of artificial intelligence that had the ability to play chess and was an expert at it. This IBM supercomputer was the first machine to win a game of chess against the world champion with regulation rules and time.

Deep Blue was programmed to identify the pieces on the chessboard and knew how each piece could move. Deep Blue could also predict what it should do in its next move and what the opponent might do. But because Deep Blue is a reactive machine, it could not learn from previous games or moves.

Memoria Limitada

The next category of artificial intelligence is limited memory. Memory-limited AI has the ability to look into the past to make current decisions and solve problems.

Limited memory AI uses data, predictions and memory to make better decisions and predictions. Limited memory has three types of models which are reinforcement learning, short-term memory (LSTM) and generative adversarial networks (GAN).

Reinforcement learning means that this category of AI can make better predictions through trial and error. These computers can learn to play chess and other games.

Computers with short-term memory (LSTM) predict the next elements of a sequence. The computer organizes the data so that the most recent information it obtains is more critical and important than past information.

Redes Generativas

Generative adversarial networks take two neural networks and make them compete against each other to be more accurate with their data and predictions. Most GANs can use a zero-sum framework to learn and make decisions.

Artificial intelligence based on theory of mind is still in the research and development phase, but it will be able to understand the people or things it communicates with.

In psychology, "theory of mind" means that people have thoughts, feelings and emotions that affect their behavior. Researchers want to create an artificial intelligence that is capable of doing and understanding this concept.

Future AI must learn that everyone has these thoughts, feelings and emotions so that these systems can be more communicative with humans. Currently there are only programs that can use a Theory of Mind simulation in simple situations.


El último paso de la inteligencia artificial será la categoría de autoconsciencia y es una extensión de la IA de la teoría de la mente.

This form of AI will be representations of themselves that will not only understand consciousness but will have it.

These forms of AI will have the ability to know their own internal states and predict the feelings of other AI or people.

These forms of AI will start without knowledge so that they can learn from experience and make their own decisions. Since they will learn from experience and have no prior knowledge, they will form their own opinions and ideas.

Benefits of AI and how it improves processes

The benefits of artificial intelligence are many, and it has revolutionized and changed the way we have performed certain processes and tasks for decades. Among the benefits of AI are automation, intelligent decision making, improved customer experience, faster and more accurate analysis of research data, and increased business efficiency. One of the benefits of AI is automation.

Automation consists of making a system or process work automatically. This has increased production rates, increased productivity, made the use of raw materials more efficient and reduced lead times in companies.

AI can make intelligent decisions by analyzing previous data quickly and efficiently. Intelligent decision making can coordinate data delivery, analyze trends, develop data consistency, make forecasts and quantify uncertainties so that businesses can make intelligent and informed decisions.

Next, improving the customer experience is a major benefit of AI. With AI, customers can have access to a company 24 hours a day.

Chatbots can respond to customer questions and complaints quickly and resolve these issues or questions efficiently. This helps to gain customer loyalty and can get feedback from customers asking simple questions about your service or products.

AI is also capable of accelerating the processing and analysis of data.

AI is much faster than a human, so it can analyze data more efficiently and with fewer human errors. Fewer errors make processes more efficient and decrease the likelihood of problems arising due to processing errors. Increased business efficiency is a major benefit of AI.

AI ensures 24-hour service because it has the ability to collect and analyze data all the time. AI also helps efficiency because its performance is consistent and reliable.

AI ensures 24-hour service because it has the ability to collect and analyze data all the time. AI also helps efficiency because its performance is consistent and reliable.

How does it work?

Artificial Intelligence systems are created by combining large amounts of data with intelligent, iterative algorithms that can learn patterns and features in the data they analyze.

When the AI system runs rounds of data processing, it tests and measures its own performance to learn and develop additional knowledge. But AI is not just one computer or one application; many processes and applications are needed for the system to mimic human tasks or skills.

There is a need for AI technology to have more accessible big data sets, graphical processing units, intelligent data processing and application programming interfaces. AI thrives the more it is used because it thrives on data.

This means that as you collect larger and more accessible data sets, you will become more reliable, faster and smarter. Graphics processing units (GPUs) are the key enabler of AI technology. GPUs enable distributed processing and can accelerate machine learning and are critical to AI's ability to perform computation in processing.

Intelligent data processing can extract data more accurately and faster, it can also read handwriting and signatures. Intelligent data processing also allows advanced algorithm AI to analyze multiple levels of data at the same time.

Application programming interfaces allow new functions to be added to computer programs and software.

This improves your ability to understand and identify patterns in the data collected.

AI in large companies

Many large companies use artificial intelligence to improve the user experience and gain a competitive advantage over their competitors. Examples of companies leveraging the use and benefits of artificial intelligence include Apple, Tesla, and Google. These companies have positioned their products above those of other companies by incorporating new AI features.


Apple integrates many different uses of AI technology into its products. The iPhone uses multiple forms of AI, such as Face ID, Siri shortcuts, and route suggestions. Face ID has made it easier to access the phone and provides a secure authentication system. Face ID uses a True Depth camera that stores accurate facial data by projecting thousands of invisible dots on the owner's face and analyzing them.

Once the AI analyzes the points it will decide whether to unlock the phone or not depending on whether it believes it owns the phone.

This AI technology increased the security of phones by implementing Face ID. Prior to Face ID, Apple used Touch ID. Touch had a 1 in 50,000 chance that a random person could unlock another person's phone, but with Face ID there is a 1 in 1,000,000 chance that a random person could unlock another person's phone using Face ID.

Siri Shortcuts is an AI-powered task sequence. This AI system automates a number of tasks and suggestions for the user, such as sending text messages or launching certain apps.

Apple's iPhone also uses AI to make route suggestions in the Maps app. The AI can help the user get around traffic during their commute and the app stores information about their usual commute or routes and can suggest them to them. This makes it easier for the user when they get in the car to get suggested directions to where they are most likely to go. These AI systems have helped Apple accelerate in the technology industry and stay ahead of its competitors. Translated with www.DeepL.com/Translator (free version)


Tesla is an American automotive and clean energy company that designs and manufactures electric vehicles. Tesla uses AI to build its cars for customization, safety, and to create features unlike any other car. Tesla uses two AI chips. Each of the chips analyzes traffic and dangerous situations differently. The analyses are then compared and the vehicle is guided based on the results. Another AI feature in Tesla vehicles is Autopilot. This function allows the vehicle to steer, brake and accelerate by itself.

The autopilot uses a deep AI neural network. This means that it uses cameras, sensors and radar to analyze the area around the vehicle.

The AI uses these features to be aware of its surroundings and processes information and data in milliseconds to ensure safe driving. This does not make the vehicle a self-driving car, but Tesla continues to research ways to make this possible.


Google has used artificial intelligence not only in its products, but also in its search engines. Google first implemented AI in 2015, when it created a new search engine called RankBrain. This was a machine learning algorithm used to sort search results and understand queries.

RankBrain knows how to change the algorithm itself, so it no longer has to be hand-coded. RankBrain can increase and decrease link importance, content length and content freshness based on keywords. RankBrain's two main tasks are to understand search queries or keywords and to measure and collect data on how users interact with search results.

RankBrain first shows the user a set of keyword-based search results and then pays attention to how the user interacts with the results offered. It looks at dwell time, organic click-through rate, bounce rate and pogo to determine user satisfaction.

Google also sells products that use AI technology. Google Home uses natural language processing and machine learning to listen to the user and make suggestions or take action based on what the user has asked for. Google Home can play music, give the user a weather report, control speakers, lights, cameras and much more.

As a smart speaker, Google Home can perform certain tasks by giving it voice commands or using the app.

Artificial intelligence capabilities have transformed the world of technology and the way we have performed tasks over the past few decades. It has changed the way we perform everyday tasks because many repetitive tasks can now be performed by artificial intelligence.

Every day we encounter AI and its benefits, such as unlocking your phone with Face ID or even just searching for something on Google. With Google Home, the user can already control many aspects of their home with voice controls or through an app.

AI has made our lives easier by making tasks simpler or even making us not have to do them at all by automating them. Many companies have started to incorporate AI due to the fact that it can make intelligent decisions, improve customer experience, create faster and more accurate research data analysis, and increase business efficiency and in turn, these benefits save the company time and money.