Corrado De Bari
Developer Evangelist, Messaging and Microservices, Oracle Database
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Developer Evangelist in MAA Platform Engineering team at Oracle, with more than 25 years of experience in Information Technology, he is currently focused on Microservices with Converged Oracle Database. In Oracle Italy since 2010, he joined Technology Sales Consulting team, working on Italian large and medium accounts on OCI, AI/ML, DataLakes and BPM/SOA platforms. Formerly Sales Engineer at Sun Microsystems, as well as Java & Software Ambassador for Italy, starting his career as architect in Telecom Italia Mobile. He holds the CEFRIEL Master in Information Technology and a bachelor's degree in Computer Science.
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Text-to-SQL: chat with a DB exploiting the Generative AI
The endeavor to translate natural language queries into SQL has been a long-standing objective within the realm of computational linguistics and database management. Recent advancements in Generative Artificial Intelligence mark a pivotal moment in this journey. Current benchmarks have showcased that Large Language Models (LLMs) extend their utility beyond mere code generation to embrace specialized tasks such as Text-to-SQL conversion. This seminar aims to explore the cutting-edge developments in this field, highlighting effective methodologies based on frameworks that transcend the traditional tools and languages commonly associated with data science, like Spring Boot and the innovative "Spring AI" APIs, showing how these modern frameworks can facilitate equally the development of a bridge between natural language processing and database interaction.
Java meets Generative AI: build a knowledge management system with Spring AI
Generative AI and its applications are no longer just a prerogative of data scientists using Python, but with Java and SpringBoot skills it could be approached through "Spring AI" API.
We will see step-by-step how we can implement a Spring Boot application based on Retrieval Augmented Generation (RAG) with: cloud, hybrid or on-premises LLM models, using a knowledge base stored in a VectorDB, showing tips&trics in ingestion, choosing the LLMs models and prompt engineering. The transition phase to production, through a Backend platform, will not be overlooked.
Corrado De Bari
Developer Evangelist, Messaging and Microservices, Oracle Database
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