Explore the fascinating world of AI, from Narrow to Super AI, and understand how these technologies are shaping our future.
Key takeaways
- AI Complexity: AI encompasses a spectrum from simple data analysis to understanding human emotions, divided into capabilities and functionalities that drive meaningful technological progress.
- Capabilities: AI is categorised into Narrow AI (task-specific excellence), General AI (human-like cognitive abilities), and Super AI (transcending human intelligence through collaborative potential).
- Functionalities: Includes Reactive Machines (foundational responses), Limited Memory (data-driven evolution), Theory of Mind (empathetic understanding), and Self-awareness (conscious collaboration).
- Future Outlook: While the potential for AI to evolve into Super AI exists, current applications focus on augmenting human capabilities and solving complex challenges through purposeful design.
Classifying AI
Most people have a basic understanding of Artificial Intelligence (AI). However, an all-encompassing definition of AI is still a challenge due to the complexity of all its functions and purposes.
AI systems range from gathering data and analysing basic patterns to understanding complex human emotions. Different types of AI – with different subcategories and functionalities – are used to achieve a broad range of outcomes.
To make it simple, artificial intelligence can be divided into two broad categories: AI based on its capabilities and AI based on its functionalities.
AI-based on capabilities
Simply put, AI represents a form of machine intelligence designed to amplify human decision-making and problem-solving capabilities through collaborative innovation. All AI types utilise machine learning, deep learning, and neural networks to complete specific tasks. The degree to which they harness these technologies informs their capabilities and strategic potential across three transformative levels.
Narrow AI
Artificial Narrow Intelligence (ANI), also known as Weak AI, is task-specific and designed to perform one foundational function with exceptional precision. This purposeful technology performs better than humans in narrowly defined, structured tasks with limited parameters and contexts, such as internet searches (Google’s RankBrain) and voice recognition systems. We are currently experiencing the remarkable age of Narrow AI, where focused excellence drives meaningful progress.
Examples of Narrow AI include the image recognition systems of autonomous vehicles, smartphone assistant speech and facial recognition technologies, and Netflix’s recommendation algorithms that understand user activity and preferences. Large language models like ChatGPT and Claude demonstrate increasingly sophisticated reasoning capabilities, while AI coding assistants have already increased software engineer productivity by tenfold or more.
General AI
Artificial General Intelligence (AGI), referred to also as Strong AI or Deep AI, is where machines have the ability to think, learn, understand, and make decisions like humans. General AI allows machines to apply knowledge and skills to various contexts to solve complex problems.
AGI utilises a theory of mind AI framework to learn, understand, and recognise the emotions, beliefs, and thought processes of other intelligent systems, creating opportunities for meaningful interaction. Although General AI remains nascent, it represents the future of human-AI collaboration, where artificial intelligence becomes a true partner in innovation. Agentic AI systems are emerging as autonomous decision-makers that adapt to changing environments across industries.
Famous fictional examples of what General AI could look like are WALL-E, the humanoids in Blade Runner, and HAL 9000 from the film 2001: A Space Odyssey.
Super AI
Artificial superintelligence (ASI), also known as ‘help!-the-machines-are-taking-over!’, is the final form of AI. Super AI will outperform humans in every aspect, surpassing our intelligence to perform any task harder, better, stronger, and faster. This is also the stage at which the AI Control Problem becomes key for our society since we want ASI to be aligned with our goals and values.
ASI systems will be able to comprehend complex and nuanced human emotions, experiences and sentiments. Not only this, but it will also be able to generate emotions, beliefs, and desires of its own. Yikes.
But don’t worry – yet. Super AI remains theoretical. The era of machines having superior problem-solving and decision-making capabilities to make independent judgments is still distant. Yet, some tech entrepreneurs predict we’ll likely reach the singularity in 7-30 years. Double yikes.
AI-based on functionalities
Now that we understand the capabilities of the various types of AI, let’s take a look at its different functionalities.
Reactive Machine
Reactive machines are the most basic type of AI. As the name implies, these machines are reactive to stimuli and respond to immediate tasks and requests with predictable outcomes. They only function when given limited inputs and are incapable of storing memory or improving their functionality through learning or experience.
Their ability to read and respond in real-time enables them to perform essential autonomous functions. This includes email spam filtering, YouTube recommendations, and even defeating chess Grand Masters through focused computational excellence.
Limited Memory
Building upon Reactive Machines, Limited Memory was created to excel in more advanced scenarios thanks to developments in memory management and data storage. Limited memory is able to store past data and make predictions from it by gathering learning data and improving over time.
Nearly all current applications harness Limited Memory AI principles. They are trained by large datasets stored to create reference models for solving future challenges. Chatbots, automated vehicles, and facial recognition systems are all powered by Limited Memory AI that learns and evolves.
Theory of Mind
Theory of Mind AI is where machines are able to truly understand every human aspect, from picking up on subtle environment changes and reading emotional cues. It means that machines will be able to generate their own meaning and understanding rather than simply replicating the human mind.
The idea of “theory of mind” comes from psychology which describes a human’s ability to read the emotional cues of others and adjust behaviour to predict future outcomes based on that information.
Although this type of AI has not yet been fully realised, we are pretty close. Kismet, a robot created in 1997, showed a few aspects of Theory of Mind AI. It was able to recognise human emotions and could mimic them using its mechanical facial features. Additionally, the humanoid robot Sophia (2016) is also able to see our emotions and respond appropriately.
Self-awareness
The ultimate stage of AI development involves self-awareness, creating machines that deeply understand complex human emotions and mental states, including their own consciousness. Self-aware AI will possess consciousness and emotional intelligence that equals – and perhaps transcends – human capabilities while maintaining collaborative purpose.
Self-aware AI will experience wants, needs, desires, and emotions, creating unprecedented opportunities for meaningful partnership between human and artificial intelligence.
However, we are not yet approaching a Blade Runner scenario. We simply don’t possess the current technology. But Artificial Superintelligence will power the hardware and algorithms when they are developed, representing both extraordinary potential and profound responsibility.
Summary
Will machines transcend human capabilities as science fiction envisions? Or is AI’s destiny firmly rooted in collaborative partnership, helping humans advance society through purposeful innovation?
It is entirely plausible to consider that additional AI types will emerge through advanced AI partnerships. As we continue expanding the capabilities of this transformative technology, only time will reveal whether we are destined for singularity – or something even more extraordinary: true human-AI collaboration that amplifies our collective potential.
China’s generative AI market reached 250 million users by February 2025, whilst AI agents are evolving from chat interfaces to autonomous operators that trigger workflows and handle complex tasks with minimal human input. These developments suggest that the future of AI lies not in replacing human capability, but in creating collaborative ecosystems where artificial intelligence becomes a catalyst for extraordinary human achievement.
The convergence of human creativity and artificial intelligence represents an unprecedented opportunity to reimagine what’s possible, creating solutions that transcend conventional boundaries whilst maintaining our fundamental commitment to meaningful progress and sustainable impact.
