Building Multimodal Question-Answering (RAG) System with Gemini

Leverage the power of Gemini for Financial Analysis!

Dive deep into Gemini's 2M context window and multimodal input capabilities with leading LLM and GenAI expert, Lavi Nigam from Google.

You'll explore:

Vertex Gemini API
Vertex text-embeddings
Gemini's cross-modal reasoning capabilities

And discover how they can help you transform your financial analysis.

Abstract:
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.

Speaker and Presenter Information

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.