AI is like giving a brain 🧠 to a machine 🤖, so it can do smart things just like people do.

💡 For example, AI is used in everyday life to:

  • Understand voice commands – like Alexa responding to what you say.
  • Recognize faces in photos – such as Facebook automatically tagging people.
  • Drive cars automatically – like Tesla’s autopilot feature.
  • Recommend content – for example, YouTube or Netflix suggesting videos based on your interests.
  • Predict what you’re typing – like when your phone suggests the next word as you type.
  • Play music on command – you say “play music,” and your smart speaker plays your favorite song.

AI can be categorized into 2 types:

  1. Weak AI(Narrow AI)🧠
  2. Strong AI(General AI)🧠💡

🧠 Weak AI (Narrow AI)

Weak AI (also called Narrow AI) is a type of artificial intelligence built to do one specific task, like:

  • Answering questions
  • Writing content
  • Recognizing faces
  • Recommending videos

It may seem smart, but it doesn’t actually understand or think like a human — it just follows patterns and rules.

✅ Examples:

  • Siri or Alexa
  • ChatGPT, Gemini

🧠💡 Strong AI (General AI)

Strong AI is a type of artificial intelligence that can think, understand, and learn like a real human.

It wouldn’t just follow instructions — it would truly understand things, make its own decisions, and even feel emotions.

🚫 Important: Strong AI does not exist yet. It’s still a goal for the future — more like science fiction for now.

👉 Levels of AI: From Zero to Superhuman

AI systems can be understood in 6 levels, ranging from no intelligence to beyond human abilities:

  1. Level 0: No AI The system is fully manual and doesn’t use any intelligence.

  2. Level 1: Beginner AI Works about as well as a new learner or unskilled person (like what we see in most AI today).

  3. Level 2: Average AI As good as a skilled human doing the job reasonably well.

  4. Level 3: Expert AI As smart and capable as top professionals in the field.

  5. Level 4: Master AI Better than almost all humans, performing at the 99% level.

  6. Level 5: Superhuman AI Smarter and faster than any human on Earth.

The Anatomy of AI

Artificial Intelligence (AI) is like an umbrella. Under it, there are smaller branches that go deeper and deeper. Let’s break it down.

AI and Its Subsets

🤖 Artificial Intelligence (AI)

AI means making computers act smart — like solving problems, making decisions, or learning. It uses logic, rules, and decision-making steps.

📚 Machine Learning (ML)

ML is a part of AI. It teaches computers to learn from data instead of following hardcoded rules. It’s like training a computer to guess patterns.

Some common ML methods are:

  • Linear Regression (LR) – finds trends in numbers.
  • Decision Tree (DT) – makes decisions by asking “yes” or “no” questions.
  • Support Vector Machines (SVM) – separates data into groups.
  • Clustering (CA) – groups similar things together.

🧠 Deep Learning (DL)

DL is a part of ML. It uses brain-like structures called neural networks. It learns from lots of data to understand complex things like photos or speech. It became popular after 2006 with faster training methods.

🗣️ Natural Language Processing (NLP)

NLP helps computers understand human language — like reading, writing, or talking. It uses AI, ML, and DL together to work with text and speech.

🏗️ Foundation Models (FM)

Foundation Models are powerful AI models trained on huge amounts of data. They are like **all-rounders – instead of being trained for one task, they can be fine-tuned to do many different things without starting from scratch.

Examples include GPT and BERT.

FM includes different types of models:

  • Language Models (LM) – Understand and write human language (e.g., ChatGPT).
  • Vision Models (V) – Understand images (e.g., for face or object recognition).
  • Audio Models (A) – Work with sound (e.g., text-to-speech like WaveNet).
  • Scientific Models (S) – Help in research, like AlphaFold for predicting protein shapes.

Think of it like this…

🤖 Artificial Intelligence (AI) is the whole kitchen. It includes all the tools, ingredients, and recipes to make smart meals (or do smart things).

📚 Machine Learning (ML) is like learning to cook by following recipes. At first, you follow step-by-step, but with practice, you learn patterns — like how long to fry or how much salt to use.

👨‍🍳 Deep Learning (DL) is like becoming a master chef. You don’t just follow recipes anymore — you create your own, experiment, and still make amazing dishes. DL handles really complex meals.

🗣️ Natural Language Processing (NLP) is like talking to your smart kitchen assistant. You say, “Make pasta,” and it understands your words, finds the recipe, and starts cooking.

🤖🍽️ Foundation Models (FM) are like a super robot chef. This robot has been trained on every recipe in the world. You don’t need to teach it how to cook each meal — just tell it what you want, and it can do almost anything right away.

What are Language Models (LMs)?

Language Models (LMs) are a type of AI that can read, understand, and write human language — like English, Hindi, German, etc. That’s what modern LMs like GPT-4 or BERT do.