Explore the different types of artificial intelligence systems, from narrow AI to theoretical super AI, and their evolving impact on our lives and businesses.

The AI models we have today are still far off from how we imagined it in film. Today’s AI models rely on learning algorithms still need human intervention to process new information and perform new tasks that fall outside of its initial training.

But AI capabilities have been evolving since the development of artificial neural networks, or deep learning, back in 2012. Research that allows machines to process information much like the human brain does.

Deep Learning Models allows AI applications to learn how to perform new tasks, make decisions without human intervention. This enables tasks automation, content generation, predictive maintenance, and so much more.

In this article, we’ll dive into the different types of artificial intelligence systems, which are categorized to AI Capabilities and AI Functionalities, and how the line between realized AI and theoretical AI continues to blur in our understanding on how AI can help our daily lives or even enhance the business.

 

The Three Kinds of Artificial Intelligence Based on Capabilities

Artificial Narrow AI

 

Artificial Narrow AI, also known as Weak AI, is the only kind of artificial intelligence we have today.

Unlike its more advanced counterparts, this AI is designed to excel at a single, specific task, doing so with incredible speed and precision that often surpasses human capabilities. However, its abilities are confined to the task it was trained for, and it can't think beyond its programmed scope.

Well-known examples of Narrow AI include ChatGPT by OpenAI, Siri, and Alexa.

 

General AI

 

General AI, or Strong AI, remains a purely theoretical concept. Known as Artificial General Intelligence (AGI), this form of AI would have the capability to utilize its acquired knowledge and skills to tackle new challenges across diverse contexts without requiring human intervention for training. The idea is, AGI would be able to perform any intellectual task that a human can manage.

The best fictional example of an AGI is the AI Samantha from the 2013 film Her starring Joaquin Phoenix and Scarlet Johansson. Samantha, voiced by Scarlet Johansson, is an AI that is not limited to single tasks—like Narrow AI—Samantha is able to hold conversations, compose music, reflect on her own existence, and evolve beyond human understanding. Samantha can learn and grown emotionally and intellectually in the film, Samantha can also show empathy, creativity, self-awareness, and general reasoning.

 

Super AI

 

Artificial Superintelligence, much like AGI, exists only in theory. If realized, Super AI would possess the ability to think, reason, and learn at a level far superior to human beings. Its cognitive ability would extend beyond understanding human emotions and experiences to developing its own emotions, needs, beliefs, and desires. Such an AI would surpass human capabilities in every intellectual aspect.

The best example of Super AI is from the latest Mission Impossible movie called The Entity. The Entity, in Mission: Impossible — Dead Reckoning and Mission: Impossible — Final Reckoning, is an Artificial Superintelligence that not only processes data but has it conscious of its own existence. It actively makes strategic decisions preserve and expand its influence. What made this fictional Super AI dangerous is its unpredictability, since Super AI surpasses the abilities and cognitive thinking of human beings, it is unpredictable and doesn’t follow clear rational patterns.

 

The Four Kinds of Artificial Intelligence Based on Functionalities

Reactive Machine AI

 

Reactive Machine AI systems are designed for highly specific tasks without the ability to retain memories of past interactions. Reactive Machine AI operate solely on current data inputs and are rooted in statistical mathematics, enabling them to analyse vast datasets and produce intelligent outputs. However, it lacks the capacity to learn from past experiences.

 

Limited Memory AI

 

Limited Memory AI differs from Reactive Machine AI by its ability to recall past events and outcomes, which allows it to monitor specific objects or situations over time. By incorporating both past and present data, it can make decisions that are more likely to achieve desired results. However, while it can temporarily remember past data, it cannot store this information long-term, and its performance enhances as it processes more data over time.

An example for Limited Memory AI is self-driving cars. These cars use recent speed, lane position, and nearby vehicle detection to make real-time driving decisions. Or customer support chatbots, where it can refer to your last message or the recent context in the conversation bet resets after the session.

 

Theory of Mind AI

 

Falling under the umbrella of General AI, Theory of Mind AI is still theoretical. This AI could tailor its interactions based on individuals' emotional needs and intentions, simulating human-like relationships. It would have the potential to grasp the nuances of art and literature, something current generative AI lacks.

Emotion AI, a subset of this category, is in development, aiming to analyse various data forms to recognize and respond to human emotions, though it hasn't yet achieved this capability.

There hasn’t been anyone who has achieved to create a Theory of Mind AI. But it has been prominent in films, like Baymax from Big Hero 6, who reads emotional cues to offer personalized care and support.

 

Self-Aware AI

 

Self-Aware AI represents a theoretical class of AI applications that would include features of Super AI. Like Theory of Mind AI, Self-Aware AI would understand its own state along with human emotions and thoughts. It would possess its own emotions, needs, and beliefs. While Emotion AI is a developing aspect of Theory of Mind AI, it aims to respond to human emotions on a deeper level, yet it hasn't fully achieved this goal.

Like the Super AI, there are no one has achieved to create a Self-Aware AI. But the same with Theory of Mind AI, Self-Aware AI is also featured in films, like The Entity in Mission: Impossible — Dead Reckoning and Mission: Impossible — Final Reckoning.

What AI Do We Use to Enhance Our Work?

As of today, we are only able to use Narrow AI (or Weak AI), including Reactive Machines and Limited Memory AI, to enhance our business processes.

Narrow AI is already part of our everyday work and interactions—especially in customer support—as more businesses look for ways to integrate AI into their operations. Some common examples include:

• Chatbots for customer service
• Predictive analytics in marketing and finance
• AI-driven tools for HR, sales, and supply chain optimization

Reactive Machines, which don’t learn from past experiences but follow predefined rules, are widely used for:

• Simple process automation, like data scanning and spam filtering
• Data sorting and tagging

Most business applications today rely on Limited Memory AI, which learns from historical data to make informed decisions in real-time. You’ll see this in:

• Recommendation engines (like Amazon, Netflix, and YouTube)
• Predictive maintenance in manufacturing
• Fraud detection in banking
• Inventory management
• Customer segmentation and targeted marketing

These AI tools may not be conscious or general-purpose, but they’re already making a big impact in streamlining operations, improving customer experiences, and helping teams make better decisions faster.

 

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