Artificial Intelligence (AI) Overview

Artificial Intelligence (AI) is transforming how we live, work, and interact with technology.
From voice assistants to self-driving cars, AI powers many innovations around us.
But AI is not just one single technology — it comes in different types, each with its own role and purpose.

Types of Artificial Intelligence Based on Capability Levels

Narrow AI (Weak AI)

  • Definition: AI built for a specific task.
  • Examples: Google Maps navigation, Alexa, spam filters.
  • Key Point: Narrow AI is highly specialised but cannot go beyond its assigned role.

General AI (Strong AI)

  • Definition: AI that can learn and perform any task like a human.
  • Examples: Still theoretical.
  • Key Point: Would allow machines to adapt knowledge across domains.

Super AI

  • Definition: AI that surpasses human intelligence in all aspects.
  • Examples: Hypothetical, often seen in sci-fi.
  • Key Point: Raises questions around control, ethics, and human safety.

Types of Artificial Intelligence Based on Functional Approaches

Reactive Machines

  • Works only in the present, no memory.
  • Example: IBM’s Deep Blue chess computer.

Limited Memory

  • Learns from past data to make better decisions.
  • Example: Self-driving cars observing road conditions.

Theory of Mind AI

  • Aims to understand human emotions and intentions.
  • Still under development in robotics and conversational AI.

Self-Aware AI

  • Future stage where AI develops consciousness.
  • Currently only theoretical.

Types of Artificial Intelligence Based on Application Domains

Machine Learning (ML)

  • AI that improves through data training.
  • Example: Fraud detection in banking, recommendation engines.

Natural Language Processing (NLP)

  • AI that understands and generates human language.
  • Example: Google Translate, chatbots.

Computer Vision

  • AI that interprets images and videos.
  • Example: Facial recognition, medical scans, traffic monitoring.

Robotics

  • AI + mechanical systems for physical tasks.
  • Example: Industrial robots, delivery drones.

Expert Systems

  • AI that uses rule-based reasoning.
  • Example: Medical diagnosis systems.

Generative AI — The Creative Side of Artificial Intelligence

Generative AI is one of the most exciting areas of artificial intelligence today.
Unlike traditional AI, which classifies, predicts, or automates tasks, Generative AI creates new content — text, images, audio, code, and even video.

How it Works: Generative AI uses advanced models (like GPT, DALL·E, Stable Diffusion) trained on large datasets to produce original outputs.

Generative AI Examples

  • ChatGPT → generates human-like text.
  • DALL·E & MidJourney → create artwork from text prompts.
  • GitHub Copilot → writes code suggestions.
  • Runway → AI-powered video editing.

Generative AI Applications

  • Marketing → auto-generated ad copy, designs.
  • Education → personalised study materials.
  • Entertainment → story writing, music, movies.
  • Business → creating reports, customer emails.

Why it Matters: Generative AI blurs the line between human and machine creativity, opening huge opportunities but also raising concerns around misinformation, copyright, and ethics.

Conclusion: The Future of Artificial Intelligence

Artificial Intelligence can be understood in different layers — from basic reactive systems to cutting-edge generative models.
While most of us interact daily with Narrow AI and Limited Memory AI, the rapid rise of Generative AI shows how fast the field is evolving.

The key lies in balancing innovation with responsibility, ensuring AI serves as a tool that makes life simpler, smarter, and more creative — while addressing the ethical challenges it brings.