Artificial Intelligence (AI) is a field of computer science that enables machines to simulate human intelligence, such as learning from data, reasoning, understanding language, recognizing patterns, and making decisions

How AI Works?

Systems capable of performing tasks that typically require human intelligence.

Systems or machines that operate independently with minimal or no human intervention.

-Decision-making -Rule-based logic -Problem solving -Pattern recognition -Language understanding

learn patterns from data

-Handles images, voice, video, text -No need for manual feature engineering -Learns representations automatically

-Text (emails, code, reports) -Images (art, designs) -Audio (music, voice) -Video

Generative AI models are trained on huge datasets, such as: -Books, articles, websites (for text) -Images and captions (for vision models) -Code repositories (for coding models)

core of Generative AI is a neural network, most commonly a Transformer architecture. Key ideas: - Neurons → small math units that detect patterns - Layers → progressively understand deeper meaning - Attention mechanism → focuses on what matters most in a sentence

Before processing, everything is broken into tokens: - Words - Parts of words - Symbols or characters

Generative AI does not think or reason like humans. It works by: - Looking at your input - Predicting the next most probable token - Repeating this step extremely fast

After base training, models are: - Fine-tuned on specific tasks - Trained with human feedback - Aligned for safety, usefulness, and tone

When you type a prompt: - Your text is tokenized - Model analyzes context - Predicts next tokens - Produces coherent output - Applies safety & quality filters

Too Vague

Missing Context

Overloaded & Confusing

Why writing good Prompt is Important?

Markdown Prompting Technique

CoStar Prompting Technique

Chain of Thoughts Prompting Technique

Prompt Chaning Framework