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Types of Generative AI

(Text, Image, Audio, Video, Multimodal)

Generative AI can work with different forms of data — and each type uses specialized models and techniques. Here’s a detailed breakdown you can teach.


1. Text Generation

Definition: Creating new text content that is human-like, coherent, and context-aware.
Examples:

  • Writing blog posts, product descriptions, poetry, stories
  • Answering questions conversationally (chatbots)
  • Code generation

Popular Tools & Models:

  • ChatGPT (OpenAI GPT models)
  • Claude 3.5 (Anthropic)
  • Gemini (Google DeepMind)
  • GitHub Copilot (code generation)

Real-Life Uses:

  • Automating customer support
  • Drafting marketing content
  • Assisting programmers

2. Image Generation

Definition: Creating images from scratch or transforming existing ones based on prompts.
Examples:

  • Creating AI artwork or illustrations
  • Designing ad banners, posters, product mockups
  • Image-to-image transformation (turning a sketch into a realistic photo)

Popular Tools & Models:

  • DALL·E (OpenAI)
  • Midjourney
  • Stable Diffusion (open-source)
  • Adobe Firefly

Real-Life Uses:

  • Advertising creatives
  • Game art design
  • Virtual interior design

3. Audio Generation

Definition: Producing new music, speech, or sound effects with AI.
Examples:

  • AI-generated music compositions
  • Voice cloning
  • Audiobook narration

Popular Tools & Models:

  • Suno AI (music)
  • ElevenLabs (voice cloning)
  • AIVA (music composition)

Real-Life Uses:

  • Podcasts & audiobooks
  • Personalized voice assistants
  • Film & game sound design

4. Video Generation

Definition: Producing video clips entirely from text prompts or editing existing videos intelligently.
Examples:

  • Creating explainer videos without filming
  • Generating cinematic scenes
  • Converting images into animated sequences

Popular Tools & Models:

  • RunwayML (Gen-2)
  • Pika Labs
  • OpenAI Sora

Real-Life Uses:

  • Ad campaign videos
  • Movie pre-visualization
  • Social media content creation

5. Multimodal AI

Definition: AI that can handle multiple input and output formats (text, image, audio, video) in one system.
Examples:

  • A chatbot that answers questions and generates images in the same conversation
  • AI assistants that understand voice, text, and visuals together

Popular Tools & Models:

  • GPT-4o (OpenAI)
  • Gemini 1.5 Pro (Google)
  • Claude 3.5 Sonnet (Anthropic)
  • LLaVA (open-source multimodal model)

Real-Life Uses:

  • Customer service with image & text support
  • AI tutoring systems (text + diagrams)
  • Virtual shopping assistants

Type of Generative AIInputOutputExample Tool
TextText promptText contentChatGPT
ImageText promptImageMidjourney
AudioText prompt / sample audioMusic / VoiceElevenLabs
VideoText prompt / imageVideo clipRunwayML
MultimodalText, image, voiceText, image, audio, videoGPT-4o

💡 Live Demo Suggestion for Class:

  • Text: Ask ChatGPT to write a news headline.
  • Image: Feed that headline into DALL·E or Midjourney to create an image.
  • Audio: Convert the headline into speech using ElevenLabs.
  • Video: Use RunwayML to create a short video of the scene.
    Students will clearly see how each type works.