Understanding Different Types of Artificial Intelligence

Artificial intelligence is an interdisciplinary branch of science that focuses on the development of machines capable of completing tasks using human intelligence. It is a term that refers to the process of simulating human intellect in robots.

The systems are specifically trained and designed to replicate human behavior and activity. The objectives of artificial intelligence include learning, reasoning, and perception. AI is being applied in a variety of areas, including healthcare, banking, and others.

Exploring the many forms of AI would provide a clear picture of the present types as well as the challenges associated with AI in future forms. So, let’s begin learning about the different types of AI.

How is AI Classified?

Artificial intelligence’s primary objective is to imitate the human cognitive process. As a result, the extent to which an AI system can mimic human capabilities is the criterion used to classify AI.

If the systems can perform more human-like activities with similar efficiency, they are regarded as more developed kinds of AI. Those forms of AI, on the other hand, that have restricted efficiency and performance are considered less advanced.

Artificial intelligence is usually categorized on the basis of two aspects: capabilities and functions.

A) Types of Artificial Intelligence Based on Capability

1. Weak AI or Narrow AI (Artificial Narrow Intelligence-ANI)

• Narrow AI comes into play when certain specific tasks need to be completed with intelligence. It is the most common form of artificial intelligence in the world.
• The narrow AI is also known as the Weak AI since the model can only execute the task for which it was trained. It is unable to perform beyond its area of expertise.
• Apple Siri, which operates on a set of pre-defined functions, is one of the finest examples of narrow AI.
• The IBM Watson supercomputer, that integrates machine learning and natural language processing with an expert systems approach, is another example.
• If Narrow AI tries to perform beyond its boundaries, it might fail in unexpected ways.
• Playing chess, product recommendations on an e-commerce site, self-driving vehicles, speech recognition, and image recognition are all examples of narrow AI.

2. General AI (Artificial General Intelligence)

• General AI is a type of intelligence machine that is capable of doing any intellectual task as good as a human.
• The purpose of general AI is to create a system that can learn and think like a human on its own.
• Currently, no system exists that can be classified as general AI and execute any work as efficiently as a human.
• Researchers from all across the world are now focusing their efforts on developing machines that can perform general AI tasks.
• Since general AI systems are still being explored, developing such systems in a full-fledged manner will take a lot of time and effort.

3. Super AI (Artificial Super Intelligence)

• Super AI is a level of intelligence at which machines may outsmart humans and perform any task better than them with cognitive capabilities. It’s an outcome of General AI.
• Some important characteristics of super AI are the ability to think, analyze, solve puzzles, make decisions, plan, learn, and communicate entirely on its own.
• Super AI is still a hypothetical Artificial Intelligence theory. The development and implementation of such systems in the real world is still a world-changing task.

B) Types of Artificial Intelligence Based on Functionality

1. Reactive Machines

• It is the most basic kind of artificial intelligence, capable of performing the simplest tasks. These are also the most primitive forms of AI, with limited capabilities.
• This form of AI does not use any kind of learning. In response to some input, the model produces some output. There is no mechanism to store any input, thus there is no way to “learn.”
• The concept is based on the human mind’s ability to respond to a variety of stimuli. There are no previous experiences that may be utilised to guide recent actions.
• The reactive machines can only do the task for which they have been designed. Beyond that, the machines are unable to function because they lack knowledge and understanding of the world.
• One of the features of these AI models is that the machines will always behave in the same way as they were designed, regardless of the time and location in which tasks are to be executed.
• AlphaGo, developed by Google, and IBM’s Deep Blue are good examples of reactive machines.

2. Limited Memory

• AI models that acquire knowledge from previously learnt information, stored data, or events are classified as limited memory types of AI.
• In addition to reactive machines’ capabilities, limited memory is capable of making judgments based on previous data.
• The mechanism of storing data or previous predictions is included in this form of AI. These data eventually facilitate making more accurate predictions.
• Large amount of training data is used to train the models. These inputs are then saved in the system’s memory as a reference model, which it utilises to solve future issues.
• Virtual assistants, chatbots, and other applications of this sort of AI can be found.

3. Theory of mind

• Researchers are actively working on developing a conceptual form of AI known as -theory of mind. The term “theory of mind” refers to machine learning models that have the ability to make a decision in the same way that a human mind does.
• This form of AI interacts with a person’s ideas and feelings. These models will take into account the fact that people’s thoughts and emotions have an impact on their behaviour.
• At present, the other types of models depict one-way relationships, such as commands given to Alexa or shouting at Google Maps when it indicates the wrong direction. However, the AI model appears to be unresponsive to any kind of behaviour.
• Social interaction is also an essential aspect of human interactions. As a result, the hypothetical machines will need to be able to recognise, understand, and remember emotional output and behaviours, as well as know how to react to them.
• Theory of mind is a little more complex, but it will result in better companions. These models are considered to be in their early stages.

4. Self-Aware

• This kind of AI signifies the final stage of AI development, that is yet to be implemented in practise and only exists in theory.
• These machines are still a fictional Artificial Intelligence idea, but once developed, they will be smarter than humans.
• The AI self-awareness concept goes a step beyond the theory of mind, with self-guided thoughts and reactions.The models will progress to a point where the system becomes self-aware. It’s one of the most important AI research.
• The models will have their own views and interests in addition to those of people with whom they engage.
• The machines will have an idea of self-preservation when they achieve self-awareness. This might lead to a situation in which artificial intelligence (AI) develops strategies to take over mankind.

The basic premise underlying the development of various forms of AI is that human intellect may be represented as symbolic operations that can be programmed by a computer system.

Different kinds of AI examples have demonstrated how well AI models can comprehend the actual world. With further development of hypothetical AI models, more advanced machines may be required to support the complexity of human cognition.