7 Types of Artificial Intelligence
Different types of artificial intelligence are being explored to automate and improve services in several sectors. AI technologies, which once seemed only part of sci-fi movies and books plot, have become part of our reality.
It has been used in different fields, for example in the process of making data-driven decisions, developing chatbots that can simulate natural human interaction, and much more. Its advancement may have a huge impact on industries' futures.
However, AI implementation has raised many doubts, mainly if it would replace human work. But, if we look at it from a different perspective, artificial intelligence, and humans can work together to accomplish better results. Human work won't become dispensable. Check out the article to know more about it.
What Is Artificial Intelligence?
"The science and engineering of making intelligent machines.", that's how John McCarthy, who coined the term in 1956, defined artificial intelligence. Despite what many people may believe, AI isn't such a new concept.
AI consists in developing computer systems that are capable of thinking like a human mind. Scientists study how the human brain functions and our cognitive processes to teach AI to follow those patterns.
Therefore, artificial intelligence becomes capable of developing tasks that demand human intelligence, such as solving complex problems and making decisions. Considering this there were developed multiple types of artificial intelligence to focus on the development of specific processes, according to their purposes.
How Artificial Intelligence Works
To be able to mimic how humans think and behave, AI gathers a massive amount of data, analyzes it, and identifies patterns to complete the tasks it was assigned to do. Its learning process consists of understanding, for example, why a decision is made, and emulating it.
Usually, professionals follow the AI development process to evaluate the answers it gives, reinforcing good decisions and discouraging the bad ones. Artificial intelligence can't be reduced to a single software or app, it's a science field. Multiple techniques, technologies, and processes are implemented to enhance AI continuously.
7 Types of Artificial Intelligence
1. Reactive Machines
The reactive machines don't store memory or learn from previous activities, therefore their capabilities are limited. As its name suggests, this type of artificial intelligence reacts to the stimulus they receive and responds to it in real-time.
They do basic autonomous tasks such as filtering spans in your mailbox or recommending movies in the streaming services you use. Another classic use for reactive machines is playing chess on the computer. The AI analyzes the move made by the player and answers back.
A known example of a reactive machine is Deep Blue, an artificial intelligence developed by IBM to play chess. In 1997, one of the most famous chess champions in the world, Gary Kasparov, played against the AI and lost the match.
2. Limited Memory
Limited memory machines have the same function as reactive machines, but they store data and learn by experience. The data kept in their memory is used as a reference to solve future problems.
For example, if AI has to name objects on an image, it will research its image database to check for patterns and identify the same items. Many AI fit in the category of limited memory, they are implemented in chatbots, self-driving cars, and virtual assistants.
3. Theory of Mind
Several studies have been developed towards amplifying artificial intelligence capacities, that's the case of the theory of mind. The idea is to create an AI that is able to comprehend thoughts and human emotions.
They would be able to interact socially and understand human needs. However, this type of artificial intelligence remains just a concept, although many researchers are working to make it viable.
Self-aware artificial intelligence, as the name suggests, is meant to be sentient and conscient. It would be able not only to perceive human emotions but think by itself, having its own beliefs, emotions, and desires.
In theory, this type of AI would be capable of developing its ideas, which is something that raises concerns. After all, self-awareness makes AI more independent and we could lose control of it, representing a danger to humankind. But, self-aware artificial intelligence remains an idea, it hasn't been created yet.
5. Artificial Narrow Intelligence (ANI)
Artificial narrow intelligence includes all AI systems that can autonomously complete tasks that require human skills. They have a limited number of competencies based on what they were programmed to perform, therefore aren't able to think by themselves.
Reactive and limited memory AIs fit in this category. Some examples of ANI are voice assistants like Alexa and Siri, and image recognition software. They usually use machine learning and neural network algorithms to function.
6. Artificial General Intelligence (AGI)
Artificial General Intelligence hasn't been developed yet as it's associated with self-aware AI. In this case, the AI would have the capability to develop competencies and capabilities independently, functioning like a human being.
7. Artificial Super Intelligence (ASI)
If AGI already is a huge challenge in technology development by creating an AI system that can feel, think, act by itself, and have its own consciousness, artificial super intelligence goes even further.
The concept of ASI is that AI wouldn't just be capable of thinking and performing activities like a human mind but exceeding it. As artificial intelligence can process data faster than any human being, with self-awareness it would have the potential to develop many other skills. For now, there is no need to worry about ASI, though, since it requires a long path to become reality, and it's just in the theory field.
Artificial Intelligence Branches
To solve problems and perform several tasks, the types of artificial intelligence use different processes and techniques. The main ones are:
In the machine learning process, the machine interprets the data that was given to it, makes a complete analysis, finds patterns, and uses this knowledge to solve problems. It improves while it's being used, as it receives more information.
Deep learning can be defined as a more advanced version of machine learning. It's used to solve advanced problems. Neural networks are implemented on high-dimensional data to gather insights and determine the best solutions.
Natural Language Processing (NLP)
Natural language processing is used so the AI can comprehend human language, which can be written or oral. The computer becomes able to process words, comprehend what they mean, and follow their commands.
Voice assistants such as Alexa and Siri use NLP, you talk to them, and the AI takes an action based on what you said. NLP is also used to translate one language into another, summarize long texts quickly, customer service chatbots, and speech-to-text-dictation-software.
Robotics is the branch of AI that focuses on the development of robots. Artificial intelligence enables them to act like humans, mimic facial expressions, and make the same movements. Humanoid robots are an example of this.
An expert system program uses AI to solve complex problems by analyzing the knowledge stored in itself to find the best solution. This system is commonly used in areas that require very specific knowledge. They are often designed to assist in scientific research, and in medicine, for example with diagnosis.
The fuzzy logic approach is based on degrees of truth. AI analyzes all the information available and determines what is the best solution. Each statement has a truth value from 0 to 1 in this system, which means it doesn't deal only with the concepts of false, 0, or completely true, 1.
The way fuzzy logic works considers the human subjective way of thinking, and making decisions. It enables the system to make choices based on a range of data and its values. Fuzzy logic is used in advanced trading model software, image processing, and automotive traffic control, for instance.
Examples of Artificial Intelligence Applications
AI has been implemented in several fields to automate tasks, diminish the risk of errors, enhance productivity, and much more. As a consequence, professionals face the need of updating themselves and learning how to use artificial intelligence to their advantage.
AI in ecommerce is used to improve customer service in online stores. Many companies have installed chatbots on their websites, for example, so a person can quickly solve their doubts. AI also analyzes customers' previous interactions and purchases to recommend products and offer a more personalized experience. It also helps to identify fake reviews.
Multiple types of artificial intelligence are used to facilitate processes like sending messages to students, and organizing grading paperwork. It's also useful to transcribe lectures and images, translate texts, and summarize videos and audio. There are also cases where AI is applied to develop personalized learning techniques for different students.
Many companies, such as Tesla, Toyota, and Audi, use machine learning to train computers to behave like humans when driving, which helps to make safety tests, improve their products and prevent accidents.
Artificial intelligence has been a great ally in the health area. It is used to develop sophisticated devices that are capable of identifying cancer cells and detecting other diseases. AI receives information about a patient, including lab data, and is able to point out possible causes for the symptoms, which can be valuable to the doctor.
Humans and AI Can Work Together
Artificial intelligence may raise some doubts, mainly when we talk about self-aware AI, or AGI. But, one thing is undeniable: AI is part of reality, and multiple types of artificial intelligence are used every day by us. For example, when you set an alarm using Alexa, or when you buy online. Fighting technological development may be pointless. However, you can learn how AI works to enjoy its potential for the greater good and prevent possible problems.
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