Title: Leveraging Elastic Search for GenAI Solutions
Speaker: Shalini Kumari and Shirsha Ray
City: Bangalore
Country: India
Language: English
Type: Presentation 30-45 mins
Level: Standard
Tags: search, generative AI, Information Retrieval
Description
As part of this presentation we would like to cover the following points:
current trends in Gen AI and use-cases that are coming our way internal to a corporation and in our products
Architecture and solution design that needs Elastic Search for enabling search with LLMs like GPT
Vector DBs - comparison and when Elastic Search has the strengths
Enabling Hybrid Search with Elastic Search
Speaker Bio
Shalini designs and implements state of the art solutions in the space of Search and Information Retrieval, leveraging modern tech stack on public cloud. She is interested in components that enable semantic search for the products that she builds and is recently focusing her studies on using vectors to enable better search. Another of her recent area of work has also been methodologies to evaluate search performance across algorithms / solution stacks. Shalini has used Elastic Search for building solutions since a long time and can share a perspective across features.
Shirsha heads the ML Engineering team in Bangalore for Thomson Reuters Labs, as part of which she is leading development and deployment of well-architected, solutions in AWS and other cloud platforms for ML projects that drive efficiency and value for AI-driven features in Thomson Reuters products, platforms and business systems. She is interested in successful operationalizing and sustenance of ML solutions into live workloads. She works with communities on AI for good, societal impact projects and in the tech for D&I space. She loves to network with people who are using AI and modern tech for building a better world that is more inclusive, more digital and together a better tomorrow.
Description
As part of this presentation we would like to cover the following points:
Speaker Bio
Shalini designs and implements state of the art solutions in the space of Search and Information Retrieval, leveraging modern tech stack on public cloud. She is interested in components that enable semantic search for the products that she builds and is recently focusing her studies on using vectors to enable better search. Another of her recent area of work has also been methodologies to evaluate search performance across algorithms / solution stacks. Shalini has used Elastic Search for building solutions since a long time and can share a perspective across features.
Shirsha heads the ML Engineering team in Bangalore for Thomson Reuters Labs, as part of which she is leading development and deployment of well-architected, solutions in AWS and other cloud platforms for ML projects that drive efficiency and value for AI-driven features in Thomson Reuters products, platforms and business systems. She is interested in successful operationalizing and sustenance of ML solutions into live workloads. She works with communities on AI for good, societal impact projects and in the tech for D&I space. She loves to network with people who are using AI and modern tech for building a better world that is more inclusive, more digital and together a better tomorrow.