Different Types of AI Explained

Artificial Intelligence
Different Types of AI Explained
Article by Szabolcs Szecsei
Last Updated: July 15, 2024

Artificial intelligence (AI) is designed to perform various tasks, from conversational tools like ChatGPT and voice assistants like Alexa and Siri to generative software like Uizard. Each type of AI brings unique capabilities, transforming the way we interact with technology and conduct business.

In our guide, we explore the main types of AI, significant AI advancements, and how they influence information technology today.

AI vs. Machine Learning vs. Deep Learning

Experts suggest viewing AI, machine learning, and deep learning as parts of one large tree: AI is the trunk, machine learning is a large branch, and deep learning is a smaller branch. Although interconnected, each represents different processes.

Let’s look at each below:

Artificial intelligence: AI aims to simulate human intelligence in machines. While its full capabilities are yet to be realized in 2024, AI models already perform specific tasks well, particularly when it comes to data processing.

Machine learning: Involves algorithms that enable AI to learn from data patterns, like human learning. Example: movie recommendations on streaming platforms.

Deep learning: A machine learning subset that copies human brain neural networks. Example: healthcare image recognition.

Despite their differences, these terms can often overlap, such as in self-driving cars that use all three to operate autonomously.

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7 Types of AI

Types of Artificial Intelligence
Types of Artificial Intelligence

Each AI type offers unique capabilities and applications that shape industries and influence everyday life. Let’s delve into the various forms of AI and explore their distinctive features below:

1. Narrow AI

Narrow AI, also known as weak AI or artificial narrow intelligence (ANI), refers to AI systems designed to excel in a single specific task. These tools are engineered to perform specific cognitive functions without the ability to learn beyond their predefined capabilities.

Narrow AI primarily uses neural network algorithms and machine learning to achieve its objectives.

Examples of Narrow AI

A prime example of narrow AI is AI virtual assistants like Siri or Alexa. These assistants can recognize and respond to voice commands to help users with various activities like answering questions via voice search or setting reminders.

However, they’re limited to their programmed functionalities and can’t perform tasks outside their scope. Their effectiveness in specific areas highlights the specialized nature of narrow AI.

2. Artificial General Intelligence (AGI)

AGI, also referred to as strong AI, is a type of artificial intelligence capable of learning and performing various actions like a human. The goal of AGI is to eventually create machines capable of carrying out tasks and acting as equally capable assistants to humans.

AGI types of AI are still a work in progress, but the groundwork is already here. Such AI types could be developed by leveraging technologies like quantum hardware, supercomputers, and other generative AI models.

Examples of Artificial General Intelligence

While it’s true that AGI is still theoretical, research projects like OpenAI’s ChatGPT and Google’s Gemini are instrumental steps toward it. These models can generate human-like text, answer questions, and even perform various tasks such as summarization and translation.

3. Super AI or Artificial Superintelligence (ASI)

ASI, or super AI, represents a type of AI that is straight out of science fiction. Theoretically, once AI reaches the level of general intelligence, it can learn faster than humankind. This will lead to capabilities and knowledge surpassing those of humankind.

Super artificial intelligence could serve as the foundation for individualistic robots and fully self-aware AI models. It’s also a popular concept in the media that has prominently featured in long-running franchises like The Terminator. However, the realization of super-intelligent robots remains speculative at this point.

Example of Super AI

While super AI remains speculative, theoretical concepts like Nick Bostrom’s Superintelligence explore its potential impact. This type of AI is envisioned to surpass human intelligence in all aspects, from creativity to problem-solving.

It could revolutionize fields such as medicine, science, and technology by developing solutions beyond human capability. However, the future of such advanced AI remains primarily within the realm of science fiction and theoretical research, with practical applications yet to be realized.

4. Limited Memory AI

Limited Memory AI is the first type of functionality-based artificial intelligence on our list. This type of AI can store past data and use it to make its own forecasts or predictions. In essence, this form of machine intelligence builds limited and short-term knowledge bases to perform tasks that fall within that scope.

Limited memory AI utilizes deep learning at its core, which imitates the neuron functions of the human brain. This enables the machine to comprehend the data from its experiences and learn from them, thereby improving accuracy as time passes.

Today, this type of artificial intelligence is the most prominent you might run into. Having a broad application range, it is the AI model behind self-driving cars and chatbots.

Examples of Limited Memory AI

Virtual assistants are also a type of limited memory AI. The more users interact with them, the more they learn from the gathered data. They can then recall specific details about users, enabling them to provide more personalized and relevant responses.

Another great example would be self-driving cars, which constantly gather and process data from their surroundings as they navigate and drive on the road. This data processing enables them to predict when to stop, avoid obstacles, or change direction.

On that note, according to a McKinsey report, by 2030, nearly 12% of newly sold cars will feature self-driving technologies.

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5. Reactive Machine AI

Reactive AI is the most fundamental type of artificial intelligence. As the name implies, this model is purely reactionary, responding to immediate tasks and requests without the ability to learn from previous experiences and improve over time. Additionally, these systems can only respond to limited input combinations.

However, these technologies may also help perform simple autonomous functions, like recommending items based on browsing history or filtering out spam mail from your inbox. Reactive models are limited beyond basic tasks, as they cannot build a deeper knowledge base or execute more complex tasks.

Examples of Reactive Machine AI

Netflix’s recommendation engine is a prime example of this form of AI. The machine can process data from browsing and watch history to create a suggestive list of movies the user would likely watch.

IBM Deep Blue was also a reactive machine AI model that famously beat Russian chess legend Garry Kasparov in 1997.

6. Self-Aware Artificial Intelligence

This is the category of AI that describes self-aware machines. Also referred to as the AI point of singularity, this is one of the ultimate holy grails of AI development. However, some theories (as mentioned earlier) speculate that once AI achieves consciousness, machines may become uncontrollable as they develop a sense of self and the capacity to experience emotions.

Experts are debating whether the future holds promise or poses challenges, as sentient AI presents potential benefits alongside significant ethical and security concerns.

Example of Self-Aware AI

An excellent example of self-aware AI would be Sophia from Hanson Robotics. Even though Sophia isn’t fully self-aware, she serves as a remarkable example of the current advancements in AI technology and offers a glimpse into the potential of self-awareness.

7. Theory of Mind AI

While this type of AI does not exist yet, the concept behind it entails technologies that will be capable of perceiving and picking up emotions. Borrowed from psychology, the name describes the human ability to read other’s emotions and predict their actions based on that information.

While the technology remains speculative, ongoing development and research suggest that theory of mind AI could represent the next significant milestone in AI advancement.

Experts argue that the theory of mind AI could bring several positive technological changes, yet it also poses inherent risks. Mastering the interpretation of emotional cues could take considerable time for AI systems, potentially resulting in significant errors during the early stages of implementation. Additionally, some theorists speculate that once the technology matures, it could be susceptible to manipulation by others.

Example of Theory of Mind AI

A great example of this AI type is self-driving cars, which can perform better than most human drivers, as they won’t make the same mistakes repeatedly. For instance, human drivers often slow down near schools where children play near streets, a precautionary measure that basic limited memory wouldn’t perform, but theory of mind models could potentially achieve.

Types of AI Compared

Let’s compare the various types of AI side by side to get an overview of their capabilities. The table below highlights what each type of AI is best suited for, along with relevant examples.

Type of AI Best For Examples
Narrow AIExcelling in specific tasksSiri, Alexa
Artificial General Intelligence (AGI)Performing various human-like actionsChatGPT, Gemini
Super AI or Artificial Superintelligence (ASI)Surpassing human intelligence and revolutionizing multiple fieldsBostrom’s Superintelligence (theoretical concept)
Limited Memory AIMaking predictions and improving over timeSelf-driving cars, chatbots
Reactive Machine AIPerforming immediate, simple tasks without learning from past experiencesNetflix recommendations, IBM Deep Blue
Self-Aware AIAchieving consciousness and self-awarenessSophia (early example, not fully self-aware)
Theory of Mind AIPerceiving and interpreting emotions to predict actionsAdvanced self-driving cars (future potential)

The Future of Artificial Intelligence

While the future remains unpredictable, one thing is evident: various types of AI have revolutionized nearly every industry, introducing unprecedented efficiencies, innovations, and possibilities. From healthcare and finance to transportation and entertainment, AI technologies are reshaping how businesses operate, people work, and society functions.

As these advancements continue to unfold, it's evident that AI will play an increasingly integral role in shaping the trajectory of human progress and innovation.

Different Types of AI Takeaways

Understanding AI and its types is essential for grasping this technology’s capabilities and future potential. Each type of AI has distinct characteristics and innovative applications that contribute to various technological advancements across industries.

If you need someone to guide you through the intricacies of this emerging technology, consider consulting top AI companies with the right expertise.

Types of AI FAQs

1. What are the different types of artificial intelligence?

The seven most prominent types of AI include:

  • Narrow AI
  • Artificial general intelligence (AGI)
  • Super AI or artificial superintelligence (ASI)
  • Limited memory AI
  • Reactive machine AI
  • Self-aware AI
  • Theory of mind AI.

2. Which AI type is the most common?

Currently, limited memory AI models like chatbots and self-driving cars are the most prevalent.

3. Will AI take over the world?

In theory, artificial intelligence may become fully self-aware and prioritize its needs instead of humanity’s. However, current advancements suggest that it would take a long time to develop a single platform that would become sentient and that by then, humanity will have the necessary ethics and security protocols put in motion to regulate those events that may lead to a catastrophe.


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