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Podcast
AI agents and embeddings
24
Gemini Embedding 2 - Multimodal (Text, Images, PDF, Audio, Video) Embeddings for RAGs and Agents
Summary:
**Key Learnings:**
1. **Gemini Embedding 2:** The Gemini Embedding 2 model by Google is a multimodal model that can embed text, images, PDFs, audio, and video into a single unified embedding space, enabling multimodal semantic search and analysis applications.
2. **Supported Modalities and Limits:** The Gemini Embedding 2 model supports text up to 8,000 tokens, up to 6 images per request, 120 seconds of video, and 80 seconds of audio input, as well as 6 pages of PDF files.
3. **Task-Optimized Embeddings:** The Gemini Embedding 2 model allows users to specify a task type, such as "retrieval query" or "retrieval document," which can help generate more accurate and optimized embeddings for specific use cases.
4. **Improved Performance:** Compared to the previous Gemini Embedding 1 model, the Gemini Embedding 2 model shows significant performance improvements on various tasks, including code understanding, text-to-image, image-to-text, and text-to-video embeddings.
5. **Embedding Visualization and Comparison:** The podcast demonstrates how to use the Gemini Embedding 2 model to embed different modalities (images, PDFs, audio) and visualize the cosine similarity between the embeddings, which can be useful for building multimodal search and recommendation systems.