What is Generative AI?
Generative AI creates new content (text, images, audio, code) by learning patterns from vast datasets. Unlike traditional programming with fixed rules, Gen AI produces probabilistic, adaptive outputs.
School Analogy: Like a student who reads thousands of books and can now write original stories in any style, but sometimes makes confident mistakes.
Key Types of AI Models
- •Large Language Models (LLMs): GPT, Claude, Gemini - for text generation
- •Diffusion Models: DALL·E, Midjourney - for image creation
- •Multimodal AI: Tools that combine text, image, and audio processing
- •Audio Generation: AI composition and sound design tools
Foundation Concepts
- •Parameters: Model size/complexity (bigger ≠ always better)
- •Tokens: Text chunks AI processes (context window limits)
- •Hallucinations: Confident but incorrect outputs
- •Bias: Models reflect training data prejudices
- •Foundation Models: Large-scale pre-trained systems serving as base for applications
AI vs Traditional Programming
- •Traditional Programming: Deterministic, rule-based, predictable outputs
- •Generative AI: Probabilistic, pattern-based, adaptive but sometimes unpredictable
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