Hi there, I agree that fact-checking is not something that current generative AI models can directly solve. Therefore, we decompose this complex into five simpler steps, which current techniques can better solve. Please refer to https://github.com/Libr-AI/OpenFactVerification?tab=readme-o... for more details.

However, errors can always occur. We try to help users in an interpretable and transparent way by showing all retrieved evidence and the rationale behind each assessment. We hope this could at least help people when dealing with such problems.

I just tried similar queries as they show on their screenshots with Kagi. Basically asked it the exact same question.

While it answered a general "yes" when the more precise answer was "no", the motivation in the answer was perfectly on point and exactly the same things.

As a general LLM for regular user fastGPT (their llm service) is in my opinion "meh" (lacks conversations for instance). But it's really impressive that it contains VERY recent data (like news and articles from last few days) and always provides great references.