Types of AI

Learn how AI is categorized into Narrow, General, and Superintelligent types, as well as by cognitive capabilities such as Reactive, Limited Memory, Theory of Mind, and Self-Aware systems.

Summary

Explore two fundamental ways to classify artificial intelligence: by its capabilities and by its functional scope, with real-world examples.

8 mins
basic
introduction

Artificial Intelligence isn’t just one thing — it comes in different forms and levels. To understand how AI systems work and what they’re capable of, researchers and engineers classify AI in two main ways:

  1. By what the AI can do (functional types)
  2. By how it works (capability-based types)

In this lesson, we’ll explore both frameworks, look at real-world examples, and learn how these classifications shape the AI we use every day.

Why AI Types Matter

Different AI systems have different levels of intelligence, flexibility, and risk. Understanding what type of AI you're dealing with helps you:

  • Set realistic expectations (e.g., don’t expect Siri to solve math proofs)
  • Design smarter systems (e.g., don’t use a reactive model for forecasting)
  • Evaluate potential dangers or limitations

For a foundational understanding, check out our AI Glossary.

Classification 1: Functional Types of AI

This view classifies AI by what it can do — how “intelligent” it seems from the outside.

1.1 Narrow AI (ANI - Artificial Narrow Intelligence)

Also called “Weak AI”, this is the type of AI that exists today. It’s designed to perform a specific task — and nothing more.

Examples:

  • Google Translate
  • Spotify Recommendations
  • ChatGPT (in practice — despite being flexible, it lacks general world reasoning)

Narrow AI may seem intelligent, but it doesn’t truly “understand” the world. It just performs a narrow set of tasks using trained patterns.

1.2 General AI (AGI — Artificial General Intelligence)

AGI would be an AI system that can learn and reason across any domain — like a human.

AGI would:

  • Switch between tasks with ease
  • Understand context and nuance
  • Learn on its own from minimal examples

🚫 As of today, AGI does not exist. Some researchers believe it’s decades away; others think we’re getting closer.

Learn more in our AGI Glossary Entry.

1.3 Superintelligent AI (ASI — Artificial Superintelligence)

This is a hypothetical AI that surpasses all human abilities — in every domain: creativity, logic, strategy, emotional intelligence.

Why it matters:

  • ASI could change civilization forever
  • Raises big questions about safety and control
  • Thinkers like Nick Bostrom and Elon Musk warn about unchecked ASI

💡 Fictional examples: HAL 9000, Skynet, Marvel’s Ultron.

Classification 2: Capability-Based Types of AI

This classification looks at how AI thinks — what cognitive features it mimics.

2.1 Reactive Machines

These are the simplest AI systems. They don’t store past data. They just react to inputs.

Features:

  • No memory
  • No learning
  • Instant decisions

Examples:

  • Deep Blue (IBM’s chess computer)
  • Basic industrial robots

2.2 Limited Memory

This type learns from past data and improves over time. Most modern AI systems use this approach.

Examples:

  • Tesla Autopilot (remembers lane data)
  • ChatGPT (short-term token memory during a conversation)
  • Image recognition systems

Limitations:

  • The “memory” is limited to what was encoded in training
  • Doesn’t “remember” you from session to session

2.3 Theory of Mind

This level of AI would understand human emotions, beliefs, and intentions. It could anticipate reactions and tailor responses.

🚧 Status: Not yet achieved. Research is ongoing in affective computing and empathy modeling.

If built, Theory of Mind AI could:

  • Collaborate in teams
  • Understand sarcasm and irony
  • Adapt to social dynamics

2.4 Self-Aware AI

This is the final step: machines that are conscious of themselves.

Such AI would:

  • Understand its own existence
  • Have internal models of “self”
  • Possibly experience emotions or purpose

🧪 Currently, this is entirely theoretical — and highly controversial. We don’t know how to measure or detect machine consciousness.

Comparing the Two Frameworks

Narrow AI (ANI)

  • Functional Type: Narrow AI
  • Capability Type: Reactive or Limited Memory
  • Examples: Siri, Google Maps, Grammarly

General AI (AGI)

  • Functional Type: General AI
  • Capability Type: Theory of Mind
  • Examples: Still hypothetical

Superintelligent AI (ASI)

  • Functional Type: Superintelligent AI
  • Capability Type: Self-Aware
  • Examples: Fictional — HAL 9000, Ultron

💡 Note: One system can belong to both frameworks. For example, a Limited Memory AI is almost always Narrow AI. But a future AGI would likely require Theory of Mind capabilities.

Visual Summary

Here are two helpful mental models to remember:

  1. Function-based Scale:
    Narrow AI → General AI → Superintelligent AI

  2. Capability Scale:
    Reactive → Limited Memory → Theory of Mind → Self-Aware

You can visualize them as two axes, like this:

AI Types Classification Diagram

This diagram shows how AI systems can be classified by both their cognitive features (X-axis) and their functional capabilities (Y-axis). Most current AI systems fall in the "Narrow + Limited Memory" category.

Mini Exercise

Classify these systems:

  1. Amazon Alexa
    → Narrow AI + Limited Memory

  2. A fictional robot that debates ethics
    → General AI + Theory of Mind (hypothetical)

  3. Google Maps
    → Narrow AI + Reactive or Limited

Try thinking through others: your phone assistant, social media algorithms, or ChatGPT itself.

Key Takeaways

  • AI can be classified by function (what it does) and capabilities (how it works).
  • Most AI today is Narrow and Limited Memory.
  • AGI and Self-Aware AI are still theoretical.
  • These classifications help us understand what current AI can (and can’t) do.

Learn More