19 Types and Examples of Artificial Intelligence Explained

Types of artificial intelligence are; limited memory, self-aware, reactive, theory of mind, general, narrow and super artificial intelligence. Examples of artificial intelligence include virtual assistance, robotics, self-driven vehicles. facial and voice recognition, real-time mapping, text-editing, and social media technology.

This article discusses the types and examples of artificial intelligence, using the outline below;

-Types of Artificial Intelligence

-Examples of Artificial Intelligence

-Conclusion

 

 

 

Types of Artificial Intelligence

There are two systems of classification used to differentiate the types of artificial intelligence.

One of these systems is on the basis of the similarity of AI technology to human intelligence; and the second system of classification is based on the level of advancement and sophistication of the AI technology.

 

-Types of Artificial Intelligence Based on Similarity to Human Intelligence

The four types of artificial intelligence, based on similarity to human intelligence, are limited memory, theory of mind, self-aware, and reactive AI technologies.

1). Limited Memory Artificial Intelligence

Limited memory is a type of artificial intelligence that works by using historical data to identify trends and patterns, which are used to make decisions and execute functions.

As the name implies, limited memory is based on the storage and subsequent retrieval of data from a storage base (or a memory).

Machines that function using limited memory technology, are equipped with the abilities of reactive AI machines, as well as the ability to utilize historical data [13].

The word ‘limited’ implies that limited memory AI technology stores data only for a limited period of time [27]. This functionality makes it possible for the technology to make relevant and timely decisions.

Limited memory is one of the most basic and important types of artificial intelligence. This is because all AI technologies depend on data storage and retrieval in one way or the other.

With limited memory, artificial intelligence is trained using data that has been collected, by analyzing the data and identifying distinct patterns or trends that can be used to make future predictions.

For this type of artificial intelligence, data collection and storage is a continuous procedure. The effectiveness of limited memory AI is dependent on the ability to store data, and to make precise predictions based on the stored data.

There are various technological models designed on the basis of limited memory artificial intelligence. These include Evolutionary Generative Adversarial Networks (E-GANs), Long Short Term Memory (LSTM), and Reinforcement Learning [12].

Recent technologies have incorporated limited memory artificial intelligence into their functional framework. These include self-driving vehicles, chatbots and virtual assistants, among others [20].

Limited memory artificial intelligence works by an iterative process which consists of steps such as data-based training, model-building, model predictions, feedback, and repetition [5].

2). Theory of Mind Artificial Intelligence

Theory of mind is a conceptual type of artificial intelligence which works based on direct interaction with human emotions, preferences, needs and thoughts [7].

The word ‘conceptual’ is used to describe theory of mind artificial intelligence, because it is still a developing technological concept, and has not been fully developed or utilized [31].

Theory of mind AI is an aspect of a broader niche called artificial emotional intelligence, and is considered to be one of the most prospective types of artificial intelligence, with regards to future developments.

This is because, by interacting with human emotions, theory of mind artificial intelligence will be able to carry out functions more effectively and suitably, to meet existing needs.

In order to develop theory of mind artificial intelligence, several fields of science and technology must be integrated.

Only by doing so will it be possible to understand the mechanism of human thought, and to apply that understanding in the design AI systems.

3). Self-Aware Artificial Intelligence

Self-aware artificial intelligence, is a type of artificial intelligence that has evolved to the point of being fully independent and self-driven.

We can also describe self-aware artificial intelligence as a type of artificial intelligence that is very similar to human intelligence, therefore possessing the ability to be self-aware [26].

Like theory of mind, self aware artificial intelligence is a hypothetical concept [22]. This means that it is yet to be developed.

Also, self-aware artificial intelligence is the closest that artificial intelligence can get to human intelligence. Achieving this level of evolution will take years and numerous contributions to the field of AI technology.

4). Reactive Artificial Intelligence

Reactive artificial intelligence is a technology which works by instantaneous response of external stimuli.

This type of artificial intelligence the most basic and simplistic [9]. It constitutes one of the earliest developments in the field of AI technology, and, unlike other types of artificial intelligence, it does not store or retrieve data.

Rather, reactive artificial intelligence provides outputs to a series of instantaneous inputs. There is no elaborate learning process or pattern identification.

 

-Types of Artificial Intelligence Based on Level of Advancement

The three types of artificial intelligence based on level of technological advancement are narrow, general, and super artificial intelligence.

1). Narrow Artificial Intelligence

Also known as ‘weak AI,’ narrow artificial intelligence is a type of artificial intelligence that is designed to effectively perform a specific task [10].

It derives the qualifying term ‘narrow’ from the fact that its functions are usually restricted within a narrow, specified range.

Most current artificial intelligence technologies are of this type, as they are designed to perform distinct functions.

2). General Artificial Intelligence

General artificial intelligence is a type of artificial intelligence that has a broad range of application.

Because of its multifunctional capability, general artificial intelligence is considered to be similar in cognitive function, to human beings [11].

One of the key advantages of general artificial intelligence is that it does not require the same form of training that is required by other types of artificial intelligence. Rather, it is able to make generalizations and connections between various tasks, thereby functioning effectively for such multiple tasks.

3). Super Artificial Intelligence

Super artificial intelligence, or ‘artificial super-intelligence’ (ASI), is a type of artificial intelligence which is highly efficient, having enhanced capabilities in terms of data collection, storage, analysis, prediction and decision-making.

Artificial super-intelligence is expected to surpass human intelligence, exhibiting better cognitive and analytic characteristics [15].

It is important to note that artificial super-intelligence is a hypothetical concept [1]. Like self-aware artificial intelligence, it represents the highest level of AI technological development.

 

Examples of Artificial Intelligence

Examples of artificial intelligence include robotics, digital assistance, chatbot technology, social media, face detection and recognition, e-payment, text editing, search and recommendation algorithms, audio to text conversion, navigation systems, ad networks, automated medical diagnosis, and smart house technology.

1). Robotics

Robotics is an example of artificial intelligence, which uses data collection, analysis and prediction to perform automated, and mostly mechanical, tasks.

Most robots are comprised of moveable parts, whose mobility is controlled by an elaborate data-utilization process.

In addition to locomotion, robotics is usually equipped with predictive functionalities that make real-time decisions based on historical, limited-memory data.

An instance of the use of robotics can be found in self-driving vehicles, which use limited memory artificial intelligence to detect obstacles, as well as to perform efficient navigation.

Robotics is used in the manufacturing industry to increase the efficiency of the manufacturing process, by automating some of the key stages [29].

artificial intelligence AI
Robotics in Manufacturing, as an Example of Artificial Intelligence (Credit: Mixabest 2008 .CC BY-SA 3.0.)

 

Another area of application of robotics is in the smart building sector. AI technology has been use to develop robotic vacuum cleaners, and home automation systems [30].

2). Digital Assistance

Digital assistance is an example of artificial intelligence which is designed to play a supportive role to humans in their work.

Tools used for digital assistance are referred to as ‘digital assistants.

There are various roles played by digital assistants, across broad range of technological niches including vehicles, personal computers, internet applications, and smart buildings.

Digital assistance works alongside other AI technologies like facial and voice recognition.

Examples of digital assistance tools include Amazon’s Alexa, Apple’s Siri, Google Assistant, and Microsoft’s Cortana [6].

3). Chatbot Technology

A chatbot is an artificial intelligence software which is designed to interact conversationally, like humans.

The use of chatbot technology is prominent in the commercial sector. These chatbots are trained to play the role of customer representatives,

Natural language processing (NLP) technology is usually a core functionality of chatbots, which they use to emulate human conversational patterns. These software are used to improve the effectiveness of operations in the e-commerce industry and beyond.

4). Social Media

Artificial intelligence is used in social media applications, for real-time monitoring of data.

Some tasks performed by AI in social media include making suggestions of possible connections to users; serving customized advertisements, and monitoring content [24].

The main type of artificial intelligence that is used for social media is neural networks [19]. Neural network designs help to identify links between datasets, which are used for functions like connection recommendation.

Examples of social media companies that rely on artificial intelligence include Facebook, Instagram and Twitter [16].

5). Face Detection and Recognition

Face detection and recognition are two closely-related examples of artificial intelligence.

The two technologies also vary slightly in their function. Face detection technology identifies any human face, while face recognition is capable of identifying a specific human face.

However, both technologies make use of a similar artificial intelligence process, involving data collection, storage, analysis and prediction.

Face detection is used mostly in virtual filters for image-capturing, while face recognition is used for security purposes, such as the FaceID unlocking function for smart phones.

Face recognition detection artificial intelligence
Face detection and Recognition as an Aspect of Artificial Intelligence (Credit:  Galstyan  2017 .CC BY-SA 4.0.)

 

6). E-Payment

E-payment is an application of artificial intelligence technology, to process financial transactions through electronic devices, in a safe manner.

The purpose of e-payment is to improve the efficiency and reliability of financial transactions in the banking sector. It also ensures that these transactions are secure, by monitoring inputs using data accumulated by a machine learning mechanism.

An e-payment system uses AI algorithms to pay for services and goods without the use of cash or checks [8], thereby increasing the number of timely and legitimate transactions.

7). Text Editing

Artificial intelligence technology is used to develop text editing software, also called ‘text editors’ or ‘autocorrect’ systems.

Text editors are developed using deep learning, natural language processing, and machine learning technologies [2]. Their role is to identify errors in text spelling or punctuation, and to suggest corrections accordingly.

To achieve this, text editors are equipped with linguistic algorithms that serve as a reference for analyzing text data.

8). Search and Recommendation Algorithms

Search and recommendation algorithms are artificial intelligence commands designed to make predictions or suggestions based on historical data, to assist in keyword research.

The branch of artificial intelligence technology that is applied in search and recommendation algorithms, is machine learning [28].

In some cases, search and recommendation algorithms work by storing historical data on the recent searches of the user, which indicate the behavior and interests of the user [23].

These data help the system to understand and predict the preferences of the user, and to make recommendations during subsequent searches.

Another function of search and recommendation algorithms, is to provide high-quality search results to the user. This is possible through a combination of machine learning and natural language processing.

Basically, artificial intelligence is used to analyze datasets for a particular search term or category, and to identify the results that best meet the needs of the user.

Examples of search and recommendation algorithms include Youtube, Netflix, Spotify and Google [18].

9). Audio-to-Text Conversion

Artificial intelligence is used for audio to text conversion, through natural language processing [14].

With audio to text converters, audio data can be interpreted and converted to text.

The same technology can be used to interact with virtual assistants, as well as with search engines and databases.

10). Navigation Systems

Maps and navigators make use of artificial intelligence to collect and analyze geospatial data in real time.

By incorporating a neural network model into satellite imagery databases, artificial intelligence makes it possible to locate the best route or pathway to a particular destination [21].

Machine learning is used to identify and tag features, which provide more detail to maps, and improves the user experience. AI is also used to detect traffic congestion, in order to make recommendations on the fastest route to any destination at any given time.

11). Ad Networks

Artificial intelligence is used in online advertising, to create and optimize ads based on machine learning algorithms.

These algorithms analyze historical data of a user or a group of users, and applies the results of the analysis to provide the best ads for these users. They also optimize the method, format and position of ad placement, to suit the user.

Through AI, advertising had become much more effective, as it is made to align with the preferences of users. There are various industries where AI-driven advertising has been used; including entertainment, healthcare, telecommunications, manufacturing, energy, financial services and the pharmaceutical industry.

12). Automated Medical Diagnosis

Artificial intelligence is useful in the field of medicine, especially for treatment-management and diagnosis [17].

In order for AI to be used to diagnose medical conditions, algorithms are applied to analyze data, identifying patterns that can be used to make predictions.

Usually, the medical data is provided in the form of x-rays, CT scans, and MRIs, among others [4].

Studies suggest that artificial intelligence achieves an accuracy of about 87% in medical diagnosis [3]. Also, AI can be used to diagnose a broad range of diseases, including heart diseases and cancer.

Given the elaborate nature of medical procedures, artificial intelligence can reduce the complexity involved in healthcare.

13). Smart House Technology

In smart houses, artificial intelligence is used to establish effective interactions between smart devices, through the acquisition and sharing of data [25].

With artificial intelligence, data is collected and analyzed in a smart house, and the results of the analysis are used to make decisions and carry out functions.

By integrating different sets of data on a smart building, and using these data to make predictions and decisions, artificial intelligence increases the efficiency of smart buildings.

 

Conclusion

The types of artificial intelligence are;

1. Limited Memory Artificial Intelligence

2. Theory of Mind Artificial Intelligence

3. Self-Aware Artificial Intelligence

4. Reactive Artificial Intelligence

5. Narrow Artificial Intelligence

6. General Artificial Intelligence

7. Super Artificial Intelligence

 

Examples of artificial intelligence are;

1. Robotics

2. Digital Assistance

3. Chatbot Technology

4. Social Media

5. Face Detection and Recognition

6. E-Payment

7. Text Editing

8. Search and Recommendation Algorithms

9. Audio-to-Text Conversion

10. Navigation Systems

11. Ad Networks

12. Automated Medical Diagnosis

13. Smart House Technology

 

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