How to build Multimodal Retrieval-Augmented Generation (RAG) with Gemini

Опубликовано 16 мая 2024, 14:05

The saying ""a picture is worth a thousand words"" encapsulates the immense potential of visual data. But most retrieval-augmented generation (RAG) applications rely only on text. This session applies RAG to multimodal use cases. It focuses on embeddings and attributed question answering to retrieve data. We’ll begin with a high-level architecture and quickly dive into a practical demo. Attendees will learn to create powerful LLM-based workflows and embed them in existing applications.

Speakers: Shilpa Kancharla, Jeff Nelson

Resources:
Try Gemini in Vertex AI → goo.gle/3Vttolh

Watch more:
Check out all the AI videos at Google I/O 2024 → goo.gle/io24-ai-yt
Check out all the Cloud videos at Google I/O 2024 → goo.gle/io24-cloud-yt

Subscribe to Google Developers → goo.gle/developers

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Event: Google I/O 2024
Products Mentioned: Gemini