Arc of AI Conference
Austin, TX • March 31 - April 3, 2025
My Sessions
Fast, Highly Available, In-Memory Vector Database for AI at the Edge
Our new AI overlords have arrived, and developers have rushed to integrate cloud-based AI services into their applications. While their adoption in the cloud is facilitated by fast (usually secure) colocated access, their adoption at the edge is beginning to receive more attention. Explore the use of AI at the edge, including the infrastructure, scalability, integration and cost challenges faced. As a part of the solution, we introduce Oracle Coherence's new vector features that enable us to deploy a lightweight, highly available, distributed in-memory vector database at the edge.
Download SlidesRAG with In-Memory Java Microservices
Learn why Retrieval Augmented Generation (RAG) has emerged as a critical need to augment Large Language Models (LLMs) w/ internal, non public data. Python is usually required for GenAI programming but we will show you a native In-Memory Java approach to RAG pipelines for LLMs. Explore GenAI in an open source, fully native Java ecosystem using Helidon Microservices framework and LangChain4j to supplement GenAI LLMs with your internal, corporate data using RAG to provide more precise and accurate responses, reduce hallucinations and increase transparency and trust. Join us as we dive into Java based RAG with LLMs and shape the future of Java and AI!
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