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Tech Talk: Reap the benefits of RAG without the hassle
Speaker: Mark Hornick (Oracle)
Abstract: Generative AI-enhanced applications are becoming essential for today's businesses. The ability to ask natural language questions and get back relevant and accurate textual responses – based on documents you trust and know to be correct - is increasingly simply expected. For example, customer service chatbots aid customers and operators alike in searching resolution logs and product documentation to draft targeted responses to customer issues. But achieving this can seem like a daunting task. Select AI on Oracle Autonomous Database provides a streamlined interface that automates enabling retrieval augmented generation (RAG) – from building the vector index to the overall RAG workflow. It even automates the addition of new content to your vector index. Select AI RAG combines large language models (LLMs) and semantic similarity search (aka AI vector search) from convenient SQL and PL/SQL interfaces so you can quickly develop generative AI-enhanced applications. Join us for this step-by-step demonstration of going from raw documents to RAG-enabled responses to natural language questions and take your applications to the next level.
Speaker Bio: Mark Hornick is Senior Director of Machine Learning and AI Product Management for Oracle Database and Autonomous Database. His focus is the Oracle Machine Learning (OML) family of products and Select AI, where he leads the PM team. Mark has over 25 years of experience integrating and leveraging machine learning with Oracle technologies. He works with internal and external customers to apply Oracle’s machine learning and AI technologies for scalable and deployable solutions. He holds a Bachelor's degree from Rutgers University and a Master's degree from Brown University, both in Computer Science.

Venue:
virtual, join from anywhere.

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