Mayo Clinic’s secret weapon against AI hallucinations: Reverse RAG in action

Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More Even as large language models (LLMs) become ever more sophisticated and capable, they continue to suffer from hallucinations: offering up inaccurate information, or, to put it more harshly, lying. This can be particularly harmful in areas like healthcare, where wrong information can have dire results. Mayo Clinic, one of the top-ranked hospitals in the U.S., has adopted a novel technique to address this challenge. To succeed, the medical facility must overcome the limitations of retrieval-augmented generation (RAG). That’s the process by which large language models (LLMs) pull information from specific, relevant data sources. The hospital has employed what is essentially backwards RAG, where the model extracts relevant information, then links every data point back to its original source content. Remarkably, this has eliminated nearly all data-retrieval-base ... Read full article.