What is Artificial Intelligence?

Artificial Intelligence (AI) is a field of computer science that aims to create systems capable of performing tasks that normally require human intelligence, such as speech recognition, decision-making, and translation.

What's the difference between Weak AI and Strong AI?

Weak AI (or Narrow AI) is specialized in a single task, like ChatGPT for text. Strong AI (or General AI) would be capable of performing any intellectual task a human can, but it doesn't exist yet.

Are Machine Learning and AI the same thing?

No. Machine Learning is a subcategory of AI. AI is the overall field, while ML is an AI technique that allows machines to learn from data.

Understanding Artificial Intelligence in 5 Minutes

🎯 What You Will Learn

1AI is technology that mimics human intelligence to solve problems
2There are 2 types: Weak AI (specialized) and Strong AI (general, theoretical)
3Machine Learning and Deep Learning are subfields of AI
4ChatGPT, Midjourney, and Google Translate all use AI
5AI doesn't 'think': it calculates probabilities from data

🤖 What Exactly Is AI?

You're already using AI every day without realizing it: when Netflix recommends a movie, when Google translates a page, or when your phone recognizes your face.

Artificial Intelligence (AI) — is a field of computer science that creates systems capable of performing tasks normally requiring human intelligence: understanding language, recognizing images, making decisions, and learning from experience.

Source: Adapted from IBM + Stanford definitions

AI doesn't "think" like a human. It doesn't truly understand what it's doing. It calculates statistical probabilities based on billions of training data points. This is why ChatGPT can sometimes "hallucinate" false information.

📊 Weak AI vs Strong AI: The Differences

Comparison between narrow AI and general AI
Criteria	Weak AI (Narrow)	Strong AI (General)
Definition	Specialized in ONE task	Capable of ALL human tasks
Does it exist?	✅ Yes (ChatGPT, Siri, Alexa)	❌ No (theoretical)
Examples	Face recognition, translation	Consciousness, general creativity
Autonomy	Limited to its domain	Total (hypothetical)
Potential danger	Bias, errors	Sci-fi scenarios

🧠 Machine Learning vs Deep Learning

These terms are often confused. Here's a simple explanation:

📊Machine Learning (ML)

Automatic learning. The machine learns from data without being explicitly programmed. Example: a spam filter that improves by analyzing your emails.

🔬Deep Learning (DL)

Advanced subcategory of ML. Uses artificial neural networks inspired by the human brain. Example: image recognition, text generation (GPT), image creation (Midjourney).

Artificial Intelligence (overall field)
↳ Machine Learning (subfield)
↳ Deep Learning (sub-subfield)

🌍 Real-World AI Applications (2026)

📊 AI in Your Daily Life

Domain	Application	Technology
💬 Communication	ChatGPT, Claude, Gemini	LLM (Large Language Models)
🎨 Creation	Midjourney, DALL-E, Sora	Diffusion Models
🔍 Search	Google, Perplexity AI	NLP + Ranking AI
🚗 Transportation	Tesla Autopilot, Waymo	Computer Vision + RL
🏥 Healthcare	Medical diagnosis, imaging	Deep Learning
🎵 Entertainment	Spotify, Netflix, TikTok	Recommendation Systems

✅In Summary

AI is not magic: it's mathematics + data + computing power. It excels at repetitive tasks and pattern analysis but remains far from general human intelligence. Understanding these basics helps you use these tools better and avoid AI "hallucination" traps.

🎯 Quiz: Test Your Knowledge

Did you understand? 10 questions to validate your learning.

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