Multimodal Prompts

🎨 Multimodal Prompts: Teaching AI to See & Create

The Story of the Multilingual Friend

Imagine you have a friend who can speak every language in the world. That’s pretty cool, right? But what if your friend could also see pictures, read documents, and understand tables—all at once?

That’s what multimodal prompts do! They let AI understand multiple types of information together—not just words, but images, documents, and data tables too.

Think of it like this: Regular prompts are like talking on a phone call. Multimodal prompts are like a video call where you can talk AND show things!

🖼️ Image Understanding Prompts

What Are They?

Image understanding prompts are like asking a super-smart friend to look at a picture and tell you what they see.

Simple Example:

• You show AI a photo of a cat on a couch
• You ask: “What’s in this picture?”
• AI says: “A fluffy orange cat sleeping on a blue couch”

How to Write Great Image Understanding Prompts

Bad prompt: "What is this?"

Good prompt: "Describe what you
see in this image. Include the
main subject, colors, and any
text visible."

Better prompt: "You are a
helpful assistant. Analyze this
restaurant menu photo. List all
food items with their prices."

Real-Life Uses

Tips for Better Results

1. Be specific about what you want to know
2. Give context about why you’re asking
3. Ask follow-up questions to dig deeper

🎨 Image Generation Prompts

What Are They?

Image generation prompts are like giving detailed instructions to a magical artist who can paint anything you describe!

Simple Example:

• You say: “Draw a happy dog playing in snow”
• AI creates a picture of exactly that!

The Secret Formula

[Subject] + [Style] + [Details] + [Mood]

Example: "A golden retriever
(subject) in watercolor style
(style) playing with a red ball
in fresh snow (details) with
warm, joyful lighting (mood)"

Good vs Bad Prompts

graph TD
    A["Vague Prompt"] -->|"Draw a dog"| B["Unpredictable Result"]
    C["Detailed Prompt"] -->|"Happy golden retriever puppy running through autumn leaves, soft sunlight, photorealistic"| D["Exactly What You Want!"]

Power Words for Better Images

Common Mistakes to Avoid

• ❌ Too vague: “Make something cool”
• ❌ Contradictory: “Dark and bright at the same time”
• ❌ Too long: Paragraphs of description
• ✅ Just right: Clear, specific, 20-50 words

📄 Document Analysis Prompts

What Are They?

Document analysis prompts help AI read and understand documents like a super-fast research assistant!

Simple Example:

• You upload a 50-page contract
• You ask: “What are the key terms and deadlines?”
• AI reads everything and gives you a summary!

Types of Document Tasks

graph LR
    A["Document Analysis"] --> B["Summarize"]
    A --> C["Extract Data"]
    A --> D["Compare"]
    A --> E["Answer Questions"]

    B --> F["Give me the main points"]
    C --> G["Find all dates mentioned"]
    D --> H["How does section 3 differ from section 5?"]
    E --> I["What happens if I miss a payment?"]

Winning Prompt Patterns

For Summaries:

"Summarize this document in
5 bullet points. Focus on
[specific topic]. Use simple
language."

For Extraction:

"Extract all [names/dates/prices]
from this document. Present
them in a numbered list."

For Analysis:

"Read this contract. Identify
any risks or unusual terms
that I should be aware of."

Real-World Applications

📊 Table Analysis Prompts

What Are They?

Table analysis prompts help AI understand data in rows and columns—like having a spreadsheet expert at your fingertips!

Simple Example:

• You show AI a table of student grades
• You ask: “Who has the highest average?”
• AI calculates and answers instantly!

How Tables Work in Prompts

AI can understand tables in different formats:

Format 1: Markdown Table

| Name  | Math | Science |
|-------|------|---------|
| Alice | 95   | 88      |
| Bob   | 82   | 91      |

Format 2: CSV Style

Name, Math, Science
Alice, 95, 88
Bob, 82, 91

Powerful Table Analysis Prompts

Calculate:

"Calculate the average of
the 'Sales' column and
identify the top 3 performers."

Compare:

"Compare Q1 vs Q2 performance.
Which products improved?
Which declined?"

Find Patterns:

"Look at this data and identify
any unusual patterns or outliers
that need attention."

What You Can Ask About Tables

graph LR
    A["Table Questions"] --> B["Calculate"]
    A --> C["Filter"]
    A --> D["Sort"]
    A --> E["Summarize"]
    A --> F["Visualize"]

    B --> B1["Total, average, max, min"]
    C --> C1["Show only values > 100"]
    D --> D1["Rank from highest to lowest"]
    E --> E1["What does this data tell us?"]
    F --> F1["Suggest a chart type"]

Pro Tips for Table Analysis

1. Tell AI what each column means if names aren’t clear
2. Specify the output format you want (list, table, paragraph)
3. Ask for reasoning not just answers
4. Request verification for important calculations

🔗 Combining Multiple Modes

The real magic happens when you combine different types!

Example: Analyzing a Screenshot of a Spreadsheet

"This is a screenshot of a
sales report. Please:
1. Read all the numbers in
   the table
2. Calculate total revenue
3. Identify the best-selling
   product
4. Suggest improvements"

Example: Creating Images Based on Document Data

"Based on this product
description document, generate
an image that would work well
as a marketing banner."

🎯 Quick Reference: The MICA Framework

Remember MICA for perfect multimodal prompts:

🌟 You’re Ready!

Now you know how to:

• ✅ Ask AI to understand images
• ✅ Create amazing image prompts
• ✅ Analyze documents like a pro
• ✅ Master table data analysis

Remember: The key to great multimodal prompts is being clear, specific, and telling AI exactly what you want and in what format.

You’ve got this! 🚀