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Thursday Dec 26, 2024
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The use and scope of Artificial Intelligence don’t need a formal introduction. Artificial Intelligence is no more just a buzzword; it has become a reality that is part of our everyday lives. With companies building intelligent machines for diverse applications using AI, it is revolutionizing business sectors like never before. In this article, you will learn the different types of AI and its uses.
Artificial Intelligence is the process of building intelligent machines from vast volumes of data. Systems learn from past learning and experiences and perform human-like tasks. It enhances the speed, precision, and effectiveness of human efforts. AI uses complex algorithms and methods to build machines that can make decisions on their own. Machine Learning and Deep learning forms the core of Artificial Intelligence.
AI is now being used in almost every sector of business:
Now that you know what AI really is, let’s look at what are the different types of artificial intelligence?
Types of Artificial Intelligence
Artificial Intelligence can be divided based on capabilities and functionalities.
There are three types of Artificial Intelligence-based on capabilities -
1. Narrow AI
2. General AI
3. Super AI
Under functionalities, four types of Artificial Intelligence
First, let’s examine different types of Artificial Intelligence-based on Capabilities.
Artificial Intelligence Based on Capabilities
What is Narrow AI?
Narrow AI, also called as Weak AI, focuses on one narrow task and cannot perform beyond its limitations. It targets a single subset of cognitive abilities and advances in that spectrum. Narrow AI applications are becoming increasingly common in our day-to-day lives as machine learning and deep learning methods continue to develop.
Apple Siri is an example of a Narrow AI that operates with a limited pre-defined range of functions. Siri often has problems with tasks outside its breadth of abilities.
IBM Watson supercomputer is another example of a Narrow AI. It applies cognitive computing, machine learning, and natural language processing to process information and answers your queries. IBM Watson once out-performed human contestant Ken Jennings to become the champion on the popular game show, Jeopardy!.
Other examples of Narrow AI include google translate, image recognition software, recommendation systems, spam filtering, and Google’s page-ranking algorithm.
What is General AI?
General AI, also known as strong AI, can understand and learn any intellectual task that a human being can. It allows a machine to apply knowledge and skills in different contexts. AI researchers have not been able to achieve strong AI so far. They would need to find a method to make machines conscious, programming a full cognitive ability set. General AI has received a $1 billion investment from Microsoft through OpenAI.
Fujitsu has built the K computer, which is one of the fastest supercomputers in the world. It is one of the significant attempts at achieving strong AI. It took nearly 40 minutes to simulate a single second of neural activity. Hence, it is difficult to determine whether strong AI will be achieved shortly.
What is a Super AI?
Super AI surpasses human intelligence and can perform any task better than a human. The concept of artificial superintelligence sees AI evolved to be so akin to human sentiments and experiences that it doesn’t merely understand them; it also evokes emotions, needs, beliefs, and desires of its own. Its existence is still hypothetical. Some of the critical characteristics of super AI include thinking, solving puzzles, making judgments, and decisions on its own.
Now, let’s look at the different types of AI-based on Functionalities.
Artificial Intelligence Based on Functionalities
What is a Reactive Machine?
A reactive machine is the primary form of artificial intelligence that does not store memories or use past experiences to determine future actions. It works only with present data. They perceive the world and react to it. Reactive machines are provided with specific tasks, and they don’t have capabilities beyond those tasks.
IBM’s Deep Blue that defeated chess grandmaster Garry Kasparov is a reactive machine that sees the chessboard pieces and reacts to them. Deep Blue cannot refer to any of its prior experiences or improve with practice. It can identify the pieces on a chessboard and know how each moves. Deep Blue can make predictions about what moves might be next for it and its opponent. It ignores everything before the present moment and looks at the chessboard pieces as it stands right now and chooses from possible next moves.
What is Limited Memory?
Limited Memory AI trains from past data to make decisions. The memory of such systems is short-lived. They can use this past data for a specific period of time, but they cannot add it to a library of their experiences. This kind of technology is used in self-driving vehicles.
What is the Theory of Mind?
Theory of mind AI represents an advanced class of technology and exists only as a concept. Such a kind of AI requires a thorough understanding that the people and things within an environment can alter feelings and behaviors. It should understand people’s emotions, sentiments, and thoughts. Even though many improvements are there in this field, this kind of AI is not fully complete yet.
One real-world example of the theory of mind AI is Kismet. Kismet is a robot head made in the late 90s by a Massachusetts Institute of Technology researcher. Kismet can mimic human emotions and recognize them. Both abilities are key advancements in theory of mind AI, but Kismet can’t follow gazes or convey attention to humans.
Sophia from Hanson Robotics is another example where the theory of mind AI was implemented. Cameras present in Sophia’s eyes, combined with computer algorithms, allow her to see. She can sustain eye contact, recognize individuals, and follow faces.
What is Self-Awareness?
Self-awareness AI only exists hypothetically. Such systems understand their internal traits, states, and conditions and perceive human emotions. These machines will be smarter than the human mind. This type of AI will not only be able to understand and evoke emotions in those it interacts with, but also have emotions, needs, and beliefs of its own.
Last but not least, we might be far from creating machines that can solve all the issues and are self-aware. However, it is fitting and vital to focus our efforts toward understanding how a machine can train and learn on its own and possess the ability to base decisions on past experiences.
