Australia's Dave Norris joins us in exploring the cutting-edge techniques of Retrieval Augmented Generation (RAG) and hybrid search methods. We delve into the limitations of traditional keyword searches in the face of unstructured data like PDFs and emails, which make up a significant portion of enterprise data. By using Data Cloud and hyperscalers like Google, Amazon, and Microsoft, Dave shows how to transform chaotic data into intelligent search engines. 

The discussion highlights the role of context in AI-generated responses, illustrating this with the challenge of summarizing meetings without enough information. The episode also examines the potential of hybrid search technologies such as Agentforce and vector search, emphasizing the importance of prompt engineering in refining data retrieval. 

Through examples from Dreamforce and fictional companies, listeners gain insights into how these technologies enhance user experiences by combining semantic and keyword searches, showcasing the advanced potential of modern search innovations.

Show Highlights:

• Discussion on the limitations of traditional keyword searches in data retrieval.
• Insights into the use of Data Cloud for managing unstructured data via hyperscalers like Google, Amazon, and Microsoft.
• Examination of hybrid search techniques, including Agentforce and vector search technology.
• Focus on the importance of prompt engineering to enhance AI responses and prevent hallucinations.
• Introduction to hybrid search, combining vector and keyword search for improved precision and relevance.

Links:

Using Retrieval Augmented Generation in Data Cloud — https://help.salesforce.com/s/articleView?id=sf.c360_a_rag_overview.htm&type=5