Description
In this session, you will learn how you can leverage Gemini's 2M context window and multimodal (text, image, audio & video) input to build a question-answering system for financial analysis. You will explore Vertex Gemini API, Vertex text-embeddings and Gemini's cross-modal reasoning capabilities.
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Instructor's Bio
Lavi Nigam
ML Engineering, DevRel at Google Cloud
Lavi Nigam is a Machine Learning Engineer and ML Advocate at Google, focused on bringing Gemini, Google's cutting-edge generative AI model, to enterprises worldwide. He is also actively developing scalable LLMOPs design patterns to help businesses efficiently manage and deploy these powerful models. With over a decade of experience building and scaling ML solutions for diverse organizations, Lavi is your expert guide to harnessing the full potential of AI on Google Cloud.
Webinar
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ON-DEMAND WEBINAR: "Building Multimodal Question-Answering (RAG) system with Gemini"
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Ai+ Training
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Webinar recording
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