🌟 Original Codebase
Welcome to the "Large Multimodal Model Prompting with Gemini" course! 🚀 Unlock the potential of Gemini for integrating text, images, and videos in your applications.
Multimodal models like Gemini are breaking new ground by unifying traditionally siloed data modalities. 🖼️📝📹 With Gemini, you can create applications that understand and reason across text, images, and videos. For instance, you might build a virtual interior designer that analyzes room images and text descriptions to generate personalized design recommendations, or a smart document processing pipeline that extracts data from PDFs and generates summaries.
What You’ll Learn:
- 📊 Introduction to Gemini Models: Explore the Gemini model family, including Nano, Pro, Flash, and Ultra. Learn to select the right model based on capabilities, latency, and cost considerations.
- 🔍 Multimodal Prompting and Parameter Control: Master advanced techniques for structuring text-image-video prompts. Fine-tune parameters like temperature, top_p, and top_k to balance creativity and determinism.
- 🛠️ Best Practices for Multimodal Prompting: Gain hands-on experience with prompt engineering, role assignment, task decomposition, and formatting. Understand the impact of prompt-image ordering on performance.
- 🏡 Creating Use Cases with Images: Build applications such as interior design assistants and receipt itemization tools. Utilize Gemini’s cross-modal reasoning to analyze relationships between entities across images.
- 🎥 Developing Use Cases with Videos: Implement semantic video search and long-form video QA. Explore content summarization techniques using Gemini’s large context window.
- 🔗 Integrating Real-Time Data with Function Calling: Enhance Gemini with live data and external knowledge through function calling and API integration. Combine NLU capabilities with APIs for interactive services.
- 🌟 State-of-the-Art Techniques: Learn cutting-edge methods for utilizing multimodal AI with Gemini’s model family.
- 🔄 Cross-Modal Attention: Leverage Gemini’s ability to fuse information from text, images, and video for complex reasoning tasks.
- 🌐 Function Calling and API Integration: Extend Gemini’s functionality with external knowledge and live data for enriched applications.
- 👨💻 Erwin Huizenga: Developer Advocate for Generative AI on Google Cloud, Erwin specializes in advancing multimodal AI applications and providing practical insights for leveraging Gemini.
🔗 To enroll or learn more, visit 📚 deeplearning.ai.