17:40 - 17:45: Welcome Words 17:45 - 18:10: Near-Realtime RAG on Production Data: Bringing AI to the Data
Speaker: Alon Zelovich, Cloud Architect, Oracle
Overview: Retrieval-augmented generation (RAG) implementations are becoming increasingly popular, and there is a growing demand for these systems to operate at near-realtime speeds and at scale. In this session, we present our approach to meet these challenges by bringing the algorithms closer to the data. This involves integrating vector search capabilities with popular databases, enabling RAG implementations on production data.
Specifically, we discuss the necessity of vector data types and the development of advanced index solutions, such as graph-based or inverted-file vector indices, to handle large-scale data efficiently. By incorporating these features into existing database systems, we aim to unlock the potential for generative AI applications on a grand scale.
This session will explore the current state of vector search capabilities, RAG implementations, and other generative AI-related features in a leading database system, highlighting the opportunities and challenges of deploying near-realtime RAG on production data.
18:10 - 18:30: Professional session: Select AI - Use natural language to analyze your data
Speaker: Dor Sela, Cloud Solution Engineer, Oracle
Overview: With the rise of LLM’s textual functionalities, we also witness advances in voice tools - both transcription and generation. A combination of these technologies unlocks a new class of conversational agents - the voice agents. Their development very much resembles the conversational agents but is also different in some aspects. In this lecture ,we’ll discuss challenges and solutions of such tools
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Dor Sela
Cloud Solution Engineer
Oracle
Alon Zelovich
Cloud Architect
Oracle
Gidi Shperber
Generative AI Expert & CEO Shibumi.AI
Goren Dayan
Enterprise Presales Manager
Oracle
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