How to build Multimodal Retrieval-Augmented Generation (RAG) with Gemini
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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 → https://goo.gle/3Vttolh Watch more: Check out all the AI videos at Google I/O 2024 → https://goo.gle/io24-ai-yt Check out all the Cloud videos at Google I/O 2024 → https://goo.gle/io24-cloud-yt Subscribe to Google Developers → https://goo.gle/developers #GoogleIO Event: Google I/O 2024 Products Mentioned: Gemini
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