Google Cloud and Oracle announced their collaboration to deliver AI-powered experiences with a demonstration at Oracle CloudWorld 2024. The demonstration, called “Coffee Nirvana,” focuses on AI-powered coffee search and highlights how Retrieval Augmented Generation (RAG) can transform user experiences.
One challenge with traditional search engines is their reliance on keyword matching, which limits the accuracy and relevance of results, especially when dealing with nuanced descriptions like “a smooth, medium-roast coffee with hints of chocolate and hazelnut.” “Coffee Nirvana” addresses this issue using RAG, which enables AI to tap into vast databases of information to deliver real-time, context-specific results.
In this demonstration, Oracle Database version 23ai is deployed on Google Cloud, and coffee descriptions and user queries are transformed into numerical representations (vectors) using a Vertex AI large language model. Langchain facilitates a similarity search within the vector database (populated with sample coffee data in the Oracle database), retrieving the most relevant matches to the user’s query. The Gemini Flash model adds another layer of sophistication, refining the search based on contextual cues and nuances in the user’s description. Finally, the Google Maps API adds yet another layer of visualization, displaying the location of coffee stockists.
The “Coffee Nirvana” demonstration showcases a number of benefits of using RAG with Oracle Database on Google Cloud, including precision and personalization, natural language understanding, and real-time inventory integration.
By combining the power of LLMs with real-time, context-rich data stored in an Oracle database, this approach delivers personalized recommendations, elevating the user experience. The potential applications of this technology extend far beyond the realm of coffee, from retail and hospitality to healthcare and education. This AI-powered solution has the potential to revolutionize industries by providing tailored experiences that cater to individual needs and desires.
