Abstract: Language models like those underlying ChatGPT have already transformed human-machine interactions, but to deliver practical applications in the field of data analytics and reliable question answering, they need to couple a conversation's context to direct access to formal sources of knowledge.
Knowledge Graphs structure knowledge as interconnected nodes and edges, and can now be a source of queryable knowledge for LLM technologies. In this talk, we
demonstrate the benefits of Knowledge Graphs for enabling a more intelligent, knowledge
aware conversational AI.
We discuss real-world use cases and technical integration aspects, emphasizing how Knowledge Graphs are used to provide accurate and relevant responses by using rich domain knowledge, its provenance, and its semantic description. Attendees gain insights into how Knowledge Graphs and LLMs can work together to unlock new possibilities for conversation driven data exploration and question answering, by harnessing the rich stores of knowledge that Knowledge Graphs provide.
Bio: Sean's experience covers multiple aspects of starting and growing a software company, including holding various titles from President through to co-lead dish washer. He continues in a leadership role as CTO and serves on the board.
CTO | Cambridge Semantics