Want To Reduce RAG Hallucinations? Here’s What To Focus On
RAG pipelines can hallucinate. That means the risk of losing user trust as well as user adoption. So, how do we minimize it? What to focus on? How to improve the outcomes? Let us answer these questions for you. Hallucinating AI is common. Sometimes the users pick on it and know not to trust the insights generated at face value, other times they make the news headlines. So, if you want to prevent this inaccurate or entirely fabricated information from making news headlines out of your RAG pipeline keep reading.
Hallucinations in AI are not a result of a vivid imagination or cheeky creativity. Rather they stem from the model’s processing and interpretation of data. The only true source of wisdom and intelligence AI has is the one that it is built on. Your data in other words is the only foundation of AI’s knowledge. Sometimes this data may be open to multiple interpretations or might be misleading. If you do incorporate additional data sources to your pipeline be sure that everything is true. The fault’s in the foundation can lead to faulty insights.
AI drives logic through algorithms. Sometimes the algorithms can make AI conclude something that might be logically possible, but realistically false. So, it is essential to provide AI with rules that help it understand what kind of insights require logic and which ones need hard facts.
