Dan Selman

See from experimental results why open text formats work best for training LLMs and the problems AI has with generating complex, structured information.

See how easy it is to implement a method to convert natural language text to nodes and edges in a knowledge graph.

Docusign distinguished engineer Dan Selman runs test queries to detect which tools a large language model (LLM) uses to answer queries against knowledge graph, showing you there's more to it than Retrieval-Augmented Generation (RAG).

See how to combine structured and unstructured semantic queries and to use large language models to orchestrate question answering over a knowledge graph.

See how you can use the “chat with your data” paradigm to convert natural language to graph queries, including using semantics search over vector embeddings.

Dan Selman walks you through creating your own knowledge graph using TypeScript, open-source tools, and the Neo4J database.