Popular AI Models Overview
🤖 Text Generation
- • Google Gemini
- • GPT-4 & GPT-3.5
- • Claude (Anthropic)
- • Llama 2 (Meta)
- • PaLM 2 (Google)
🎨 Image Generation
- • DALL-E 3 (OpenAI)
- • Midjourney
- • Stable Diffusion
- • Adobe Firefly
- • Leonardo AI
Google Gemini Prompting
Gemini excels at multimodal tasks, combining text and images. Use conversational prompts with clear context.
Gemini Best Practices
- ✅ Provide clear, detailed instructions
- ✅ Use examples for complex tasks
- ✅ Leverage multimodal capabilities
- ✅ Ask for step-by-step reasoning
DALL-E 3 Prompting
DALL-E 3 understands natural language descriptions and creates highly detailed images from text prompts.
Example DALL-E Prompt
"A cozy coffee shop interior with warm lighting, wooden furniture, plants by the windows, customers reading books, in the style of a watercolor painting" Stable Diffusion Techniques
- Positive Prompts: Describe what you want to see
- Negative Prompts: Specify what to avoid
- Weights: Use (word:1.2) to emphasize elements
- Quality Tags: Add "high quality, detailed, 4k"
Model-Specific Tips
GPT-4 Advantages
- • Better reasoning and logic
- • Improved code generation
- • More nuanced understanding
- • Better instruction following
Llama 2 Characteristics
- • Open-source and customizable
- • Good for specialized fine-tuning
- • Strong performance on coding tasks
- • Requires more technical setup
Choosing the Right Model
Selection Guide
- General conversation: ChatGPT or Claude
- Code generation: GPT-4 or GitHub Copilot
- Image creation: DALL-E 3 or Midjourney
- Long documents: Claude or Gemini
- Real-time info: Bing Chat or Perplexity
Universal Prompting Principles
These techniques work across most AI models:
- Be Specific: Clear, detailed instructions work universally
- Provide Context: Background information improves all models
- Use Examples: Few-shot prompting is widely effective
- Request Reasoning: Ask models to explain their thinking
- Iterate: Refine prompts based on results