Tokyo RAG user group Meetup

Join us for an evening of short talks about Retrieval Augmented Generation!

Talks:

Intro: What is RAG? in 5 minutes

Effective RAG Evaluation Strategies (15 min)
Diego Mateos (https://www.linkedin.com/in/diego-mateos-pro/), Machine Learning Engineer, Rakuten, provides a clear guide on creating test datasets and evaluating the different components of the RAG pipeline, including the use of RAGAS. Ideal for those looking to improve their model evaluation techniques.

Deploying scalable RAG Apps in Azure (10 min)
Sudev Chirappat (https://www.linkedin.com/in/sudev-chirappat-39b91572/) , Lead, Engineering Section, Rakuten, talks about a general architecture to deploy scalable RAG applications on Azure using container apps. Learn to manage and scale your RAG applications efficiently in the cloud.

Advanced RAG Strategies with Llama Index (20min)
Pierre-Loïc Doulcet (https://www.linkedin.com/in/doulcet) , Founding Engineer, LlamaIndex, talks about how to leverage LlamaIndex to deploy advanced RAG strategies.

Trial attempt to improve the accuracy of RAG with LlamaIndex and Neo4j, a graph database / LlamaIndexとグラフデータベースであるNeo4jを利用したRAGの精度向上のトライアル
Hajime-Arai, AI Engineer, Creationline

Trial and error for in-house RAG tool implementation
Yuito Nakamori (https://www.linkedin.com/in/yuito-nakamori-023ab7160/) , AI data engineer, Data Engineering Division, Data Strategy Office, Money Forward Inc.