Building Accurate Ontologies
The importance of constructing a robust ontology on a knowledge graph is highlighted as a foundation for improving accuracy and reducing hallucinations in AI. Real-time monitoring of answer quality allows for immediate adjustments to inaccuracies, ensuring that data relationships are clearly defined and retrievable. As AI models evolve, the integration of human oversight becomes crucial in distinguishing between correct and misleading information.In this clip
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Eye on AI
The Importance of Data Quality in AI Systems
Related Questions
What are the opportunities for generative AI to help with data integrity?
Can you help me with suggesting particular paths for building and populating a Knowledge Graph using LLMs that includes time-dependent data, such as retrieving the "current" President of the USA and previous presidents? How can I use this Knowledge Graph for Retrieval Augmented Generation (RAG) to help with business goals or more clever User Interfaces (UIs)?