Addressing the Hallucination Problem

The hallucination problem is a significant challenge for large language models, which often generate plausible but inaccurate information. This occurs because these models are trained to predict the next word based on extensive amounts of text, leading them to produce confident responses that may not be factually correct. SuperFocus.ai aims to tackle this issue by narrowing the model's focus to specific domains and integrating an external memory that helps ensure responses are based on credible sources. This approach has applications in various fields, such as customer support, education, and enterprise-level inquiries, where accurate and reliable information is crucial.