Topic: knowledge graphs

Jacob Hooker of Sensorium Therapeutics speaks with Rafael Rosengarten about investigating plant-derived compounds for psychiatric and neurological drug development. They discuss ethnobotanical records, knowledge graphs and AI as tools for generating hypotheses, alongside the medicinal chemistry and clinical testing needed to turn potential leads into medicines.

Siddhant Pardeshi describes autonomous software-development systems that combine knowledge graphs and vector search to navigate large repositories. The conversation examines context engineering, agent orchestration, model-specific prompting and persistent feedback. It also considers how evaluation should reflect security, maintainability and acceptance of the resulting software.

A rich data representation that finds wide application in industry and research is the so-called knowledge graph - a graph-based structure where entities are depicted as nodes and relations between them as edges. Complex systems like molecules, social networks and industrial factory systems can be described using the common language of knowledge graphs, allowing the usage of graph embedding algorithms to make context-aware predictions in these information-packed environments.