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Online Talk

Data Streaming and Retrieval-Augmented Generation (RAG) for Generative AI

์ง€๊ธˆ ์‹œ์ฒญํ•˜๊ธฐ

Thursday, June 13, 2024

10 AM PDT | 1 PM EDT | 10 AM BST | 10:30 AM IST | 1 PM SGT | 3 PM AEST

Is your AI chatbot hallucinating? LLMs are a great foundational tool that has made AI accessible for everyone, but they lack real-time domain-specific data. Building cutting-edge GenAI applications requires an understanding of context around a query and generating relevant, accurate results.

This is where RAG comes in. RAG is a pattern that pairs prompts with real-time external data to improve LLM responses.

Join Confluent experts Andrew Sellers, Head of Technology Strategy, and Kai Waehner, Global Field CTO, as they deep dive into RAG and the 4 Steps for Building Event-Driven GenAI Applications. Register now to learn:

  • How to build a real-time, contextualized, and trustworthy knowledge base
  • Where a data streaming platform and Apache Flinkยฎ stream processing (with AI model inference) fit in the RAG architecture
  • Key steps of data augmentation, inference, workflows, and post-processing
  • How a RAG demo works, featuring an AI chatbot that provides personalized product recommendationsโ€”built using Confluent, OpenAI, ChatGPT-4, Flink, MongoDB, and D-ID

์•ค๋“œ๋ฅ˜ ์…€๋Ÿฌ์Šค(Andrew Sellers)๋Š” ์ „๋žต ๊ฐœ๋ฐœ, ๊ฒฝ์Ÿ ๋ถ„์„ ๋ฐ ์‚ฌ๊ณ  ๋ฆฌ๋”์‹ญ์„ ์ง€์›ํ•˜๋Š” ํŒ€์ธ Confluent์˜ ๊ธฐ์ˆ  ์ „๋žต ๊ทธ๋ฃน์„ ์ด๋Œ๊ณ  ์žˆ์Šต๋‹ˆ๋‹ค.

Kai Waehner is Field CTO at Confluent. He works with customers across the globe and with internal teams like engineering and marketing. Kaiโ€™s main area of expertise lies within the fields of Data Streaming, Analytics, Hybrid Cloud Architectures, Internet of Things, and Blockchain. Kai is a regular speaker at international conferences such as Devoxx, ApacheCon and Kafka Summit, writes articles for professional journals, and shares his experiences with new technologies on his blog: www.kai-waehner.de. Contact: kai.waehner@confluent.io / @KaiWaehner / linkedin.com/in/kaiwaehner.

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