Convergence of AI and Private Data

Large language models (LLMs) from companies like OpenAI, Microsoft, Google, and Anthropic are generating a lot of interest and use by the public. They are used by hundreds of millions of users. The key benefit LLMs provide is a natural language reasoning interface for humans. But LLMs have some major functional issues such as bias, reasoning errors, safety, and privacy concerns. Companies that can take advantage of their private data with LLMs will have a strong business advantage. During this webinar, we'll show you how you can: - Improve AI trustworthiness; - Capture human expertise as a re-usable knowledge graph - Add context and meaning to your data ahead of your LLM to improve results; - Support LLMs with private knowledge; - Act as an LLM-independent associative long-term secure private data memory; - Reduce LLM functional issues; - Provide security and transparency with respect to LLM responses. - Demo from Datavid Join Progress MarkLogic's Senior Customer Success Manager, Philip Miller as he hosts Imran Chaudhri, Chief Architect, Healthcare & Life Sciences to discuss how MarkLogic & Semaphore can be used to leverage private or propriety data with generative AI. Helping businesses and organizations provide context, meaning, and insight into the data used by AIs, as well as, improving and contextualizing the results. Also presenting during this session with be Datavid. Datavid Rover (powered by Progress MarkLogic and Semaphore) is a cutting-edge, extensible data platform tailored to extract and manage knowledge from a wide range of data sources. It specializes in automating real-world concept classification, crafting detailed knowledge graphs, executing natural language searches, and highlighting concealed insights. Core benefits include simplified data processes, enhanced integration, and semantic capabilities, all streamlined for faster project delivery and personalized experiences.