What is Artificial Intelligence?

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Artificial intelligence (AI) refers to systems or machines that simulate human intelligence. This allows these machines to learn and think on their own, while also being able to make decisions without human assistance.

In order to understand what is AI trying to do, itโ€™s important to take a look at its ultimate goal. This objective is to make machines that can process and assimilate data in a completely independent manner, while also possessing the ability to become self-aware of their existence.

At present, AI is far from mass-producing machines that are self-aware. But it has evolved enough where common systems and machines can operate unassisted, assess data on their own, and make decisions on their own accord.

There are different types of AI, some of which can be found in many systems and machines. By learning about these subsets of AI, you can know more about AI and how it operates.

Key Points

  • AI gives systems and machines the ability to learn, think, and make decisions on their own.
  • There are different types of AI that are each classified according to their ability to operate independently.
  • AI aims to evolve systems that can operate completely on their own while having human-like self-awareness.
  • In its simplest form, AI can only perform those tasks that it has been programmed to do. In its advanced form, AI can be an independent thinker and decision-maker.

What is AI: How Does It Work and What is It Set Out to Achieve?

AI works through systems and machines that are designed to mimic human intelligence. This includes the human ability to perceive information, analyze data, and make a decision according to their assessment. AI systems emulate these intelligent processes through a set of predefined tasks and advanced algorithms that their programmers equip them with.

Through AI, humans aim to create systems and machines such as robots that can think and act on their own by the use of available information. The eventual goal from this quest is to develop AI systems that are self-aware, self-evolutionary, and self-dependent.

AI has different categories that define the capabilities of systems and machines that operate through this mechanism. These categories make it easier for data scientists, AI programmers, and other users to determine what type of artificial intelligence approach they should use with their applications.

AI is usually segmented into the following four groups.

1. Reactive

Reactive artificial intelligence is considered the most dated form of AI. This category gets its name due to having a predefined reaction to a set of data and actions. As such, these types of AI systems do not learn from their experiences of handling information. Instead, they are only capable of processing and analyzing data according to their preset programming and reacting to it.

This limits the ability of these AI systems to form their own opinion outside of the parameters that they have been equipped with. But when trained with different interpretations of data in mind, reactive AI systems and machines can still perform marvelous and often redundant tasks on their own to make humansโ€™ lives easier.

While learning about what is AI, you may find the highly talked-about example of reactive AI in the form of the legendary Deep Blue supercomputer by IBM that was programmed to play chess and won matches against a world champion in 1996-1997. Whereas, a commonly-seen example of reactive AI is the content suggestion system of different streaming services, which analyzes the type of content that users consume and offers similar suggestions according to tags and other identifiable information.

2. Limited Memory

Limited memory AI refers to systems and machines that have the ability to draw from their previous experiences in order to make decisions in the present. This makes them a mix of reactive AI but with the capabilities of ML embedded into them. This also highlights the objectives that modern AI can achieve with more advanced approaches, while also processing complex sets of data.

Due to its categorization of using previous experiences of processing data to perform new actions, all modern AI systems and machines use the limited memory model. This makes limited memory one of the most ubiquitous forms of the types of AI that are considered sought after by data scientists and programmers alike.

Given that limited memory AI serves as the foundation of various modern systems, you can find it across several applications. Out of these approaches, self-driving vehicles stand out as the one of the most popular demonstrations of all. This also makes limited memory one of those AI types that are set to reach new heights of popularity in the near future.

3. Theory of Mind

While learning what is AI, you also need to pay attention to theory of mind systems. These AI systems and machines are not fully-formed or available in tangible consumer applications as of yet. But their concept is well-defined and opens new doors to the types of wonders that AI can achieve for machines as well as humanity in the future.

In a nutshell, theory of mind AI aims to go beyond emulating human intelligence and aspires to understand the thoughts, needs, and emotions of others. In turn, this AI evolution aspires to elevate synthetic emotional intelligence in a way that makes systems and machines understand human emotion just as well as they are able to replicate it.

With that being said, theory of mind AI is not as easy to replicate as predicting some inevitable turns on a chess board. Instead, it calls for the AI systems and machines being trained in this approach to truly analyze and assess the person whom they are interacting with. This calls for some significant progress in the current AI space, but also promises an exciting future for AI.

4. Self-Aware

Out of the four thrilling types of AI, self-aware AI is perhaps the most innovative yet contentious topic of all. Similar to theory of mind AI, self-aware AI remains under development before it can reach a level where its applications are seamless and ready for larger commercial and public use. But as the name suggests, self-aware AI systems and machines such as robots will be able to become sentient.

This perception of self-awareness will come from further advancing currently used AI systems including reactive and limited memory AI. Since AI is a rapidly evolving space that keeps bringing new systems in place, this evolution is not off the table even if it is bound to take some time.

This means that even though it will take some time for scientists and experts to understand what is AI capable of doing with synthetic emotional intelligence, the possibilities to have AI that thinks, feels, and acts like humans do will be the pinnacle of AI technology. This advancement can then be showcased in the form of robots and apps that are able to interact with humans on the same emotional level as their own species.

illustration of a cat climbing a ladder

The Different Types of AI Applications

Apart from the four types of AI mentioned above, the artificial intelligence space also has different subsets under its name. These include the following approaches.

Machine Learning

Often used interchangeably with artificial intelligence, machine learning (ML) is a subcategory of AI. AI machines that use ML actively learn from the data that they process and apply previously-learnt insights and patterns to process new sets of information in the future. These AI systems can adapt to new processes without having to follow preset instructions. This makes limited memory AI a part of ML.

Deep Learning

Deep learning is a part of ML, where it acts as the more advanced version of ML itself. As compared to ML, deep learning processes more complex and larger sets of data that can comprise different uncategorized media such as image, voice, and video. This also works for large amounts or layers of data that are overwhelming for humans to process in their original state. This makes deep learning a popular approach for limited memory AI with more advanced needs.

Natural Language Processing (NLP)

Natural language processing is now a commonly available approach for using AI, particularly machine learning. It refers to a system or machineโ€™s ability to identify, understand, and process human speech. The goal of this approach is for AI machines to emulate human speech in a way that renders them free of needing human assistance.

You may also stumble upon the following terms during your research to learn what is AI.

Neural Networks

Also known as artificial neural networks (ANNs) or simulated neural networks (SNNs), neural networks use the human brain as a model to connect different branches of complex data through layers. Neural networks are considered a subcategory of machine learning and play a vital role to power AI that works with the deep learning approach.


Perhaps the most popular iteration of AI is its representation in robotics. These machines focus on the handling and management of physical processes. This makes them popular in various settings such as manufacturing plants as well as military operations. These AI systems mostly work on preset data, but they can use different AI subsets to become more advanced.

Artificial General Intelligence (AGI)

Artificial general intelligence (AGI) is the interpretation of theory of mind and self-aware AI models. These AGI systems and machines have not been built to perfection and remain heavily under the development process for now. But once they are developed, they will redefine the actions that the current types of AI can perform all on their own.

illustration of a cat climbing a ladder

AI is Here to Stay, With Its True Potential Yet to Be Reached

With voice assistants, self-driving cars, and various administrative tools, AI has already made itself a part of our life. But its true wonder in terms of theory of mind and self-awareness is yet to be reached. As AI evolves further, these advancements may also unlock in the future and unveil the true power of human-like intelligence in various systems and machines.

Rebekah Carter

Rebekah Carter is an experienced content creator, news reporter, and blogger specializing in marketing, business development, and technology. Her expertise covers everything from artificial intelligence to email marketing software and extended reality devices. When sheโ€™s not writing, Rebekah spends most of her time reading, exploring the great outdoors, and gaming.

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