7 Types of Artificial Intelligence (AI) and Branches
AI has come a long way since its inception, the history of AI can be traced back to the mid-20th century. Alan Turing, a British mathematician and computer scientist is credited with laying the groundwork for AI in 1950.
AI refers to the ability of machines to mimic human intelligence and perform tasks that traditionally require human intelligence, such as learning, reasoning, problem-solving, perception, and natural language processing. In this blog, we will learn the different types of artificial intelligence (AI), its stages, branches of AI, and more.
What Is Artificial Intelligence (AI)?
Artificial Intelligence deals with introducing human behavior in computers or automated machines. It makes computers perform various advanced tasks or functions that a human can do. For example, the ability to analyze raw data and gather information from it. AI is the foundation of revolution in modern computing, revealing a wide range of abilities for businesses and individuals.
7 Different Types of Artificial Intelligence (AI)
Artificial intelligence can be categorized into the following different types of artificial intelligence.
1. Reactive Machines
These machines are the oldest form of artificial intelligence. They operate solely on reactions. This means that reactive machines respond to a reaction, which is an external stimulus. It reads the reaction, responds to it, and acts upon it in real-time. They are unable to retain information or improve responses based on previous external stimuli.
Machine learning models behave as reactive machines as they analyze customer data, such as search history and purchase history, and provide recommendations to the customers. For example, Deep Blue was a reactive machine developed by IBM that was able to defeat Garry Kasparov, the chess champion of 1997.
2. Limited Memory
This type of AI model suggests building a limited memory base and making improvements and predictions based on that stored information. A vast number of AI applications are used in today’s time which are limited memory AI.
All current AI systems are programmed using massive amounts of training data, which they store in memory to create a reference model for future problem-solving. For example, commonly used chatbots on various websites, automatic cars, or self-driving cars.
3. Theory of Mind
Most artificial intelligence models and machines do not possess the capability to pick up cues from human emotions or from the environment. The idea that AI will be able to understand and sense other people’s emotions completely is known as the “theory of mind”. This is a term taken from psychology that explains how humans can recognize how others feel and guess.
This capability can bring “life” to the realm of AI. For example, the theory of mind AI can help self-driving cars spontaneously recognize a busy street where kids play every day, causing no accidents.
4. Self-Aware
This is the next stage in the theory of mind in which the AI acquires the awareness of its existence and possesses the capability of feeling emotions like a human. This means machines will not just understand the emotions and thoughts of others, but also their own. This is a hypothetical concept similar to the theory of mind.
When we reach self-aware AI, we’ll have AI that has human-like awareness, is as smart as humans, and shares similar desires and feelings.
5. Artificial Narrow Intelligence (ANI)
It is known as narrow AI or weak AI because the design of ANI tools is limited to specific actions and tasks. It cannot diversify its capabilities independently beyond its design. These tools take the support of machine learning algorithms to perform a particular task.
For example, natural language processing AI can recognize and respond to only voice commands. Hence, it is an ANI because it responds to a specific task. Similarly, Siri, a virtual assistant, recognizes and responds to voice commands.
6. Artificial General Intelligence
It is also known as strong AI because artificial general intelligence machines can perform a wide variety of tasks just like humans. It is more dynamic in terms of performance. The word “general” indicates all tasks that humans can do.
The purpose behind designing artificial general intelligence is to build machines that are capable of multi-tasking and be smart helpers for humans. For example, ChatGPT, an AI-generative model is a good example of artificial general intelligence.
7. Artificial Super Intelligence
It is theorized and believed that this type of artificial intelligence will surpass the capabilities of artificial general intelligence. The performance and intelligence levels are expected to be fast-paced, surpassing human intelligence. Therefore, it is also known as super AI. This concept is hypothetical and often discussed keeping in mind the future advancement in AI.
For example, the “Skynet” character from the “Terminator” movie series. Skynet is an advanced AI system that becomes self-aware and attains superintelligence. Such an artificial superintelligence character or machine is a potential threat to humanity. So, there is less likelihood that artificial superintelligence will flourish.
You can learn more about the basics of AI through this comprehensive machine learning course.
9 Major Branches of Artificial Intelligence (AI)
Artificial intelligence is divided into several branches and below are the major branches of artificial intelligence (AI):
1. Machine Learning
It is a branch of AI that deals with the ability of a machine to analyze, interpret, and process data for resolving the problems of the real world.
2. Natural Language Processing
It provides the ability for a machine to understand human written and spoken languages or speech and synthesize it for communicating back. This can provide services to businesses and individuals. A good example of NLP is the AI chatbots used by e-commerce companies to understand reviews and improve user experience.
3. Robotics
Robotics is one of the major branches of artificial intelligence (AI). This mainly involves designing and using robots in various applications. They are automated machines based on AI reacting to real-world situations by taking liable actions. They are used in defence, manufacturing, drones, bots, and automated machines.
4. Fuzzy Logic
It is the computation based on “degrees of truth” as a substitute for “True or False” or the ‘’Boolean logic’’. It is used for resolving complex issues that require making decisions, like in the medical field, space research, automation of vehicles, etc.
5. Expert Systems
It is a program based on AI that can imitate the behavior of a human being and make a judgment based on expertise in that field. It uses the “if” and “then” logic to resolve complex issues. These systems are used in detecting viruses, analyzing loan profiles, and managing information.
6. Computer Vision
Computer vision corresponds to human vision. It allows machines to analyze visual inputs such as images and videos and retrieve meaningful information. It is generally used in analyzing X-rays, CT scans, MRI reports, building 3D models, etc.
7. Fuzzy Logic
It is the computation based on “degrees of truth” as a substitute for “True or False” or the ‘’Boolean logic’’. It is used for resolving complex issues that require making decisions, like in the medical field, space research, automation of vehicles, etc.
8. Expert Systems
It is a program based on AI that can imitate the behavior of a human being and make a judgment based on expertise in that field. It uses the “if” and “then” logic to resolve complex issues. These systems are used in detecting viruses, analyzing loan profiles, and managing information.
9. Computer Vision
Computer vision corresponds to human vision. It allows machines to analyze visual inputs such as images and videos and retrieve meaningful information. It is generally used in analyzing X-rays, CT scans, MRI reports, building 3D models, etc.
Conclusion
AI is rapidly changing the way we interact with machines and different types of artificial intelligence are used for various purposes. These different types of AI include rule-based systems, machine learning, deep learning, natural language processing, robotics, and computer vision. As technology evolves, we can expect AI to play an increasingly significant role in our lives.
