Today, we are publishing a new open source sample chatbot that shows how to use feedback from Automated Reasoning checks to iterate on the generated content, ask clarifying questions, and prove the correctness of an answer.
The chatbot implementation also produces an audit log that includes mathematically verifiable explanations for the answer validity and a user interface that shows developers the iterative, rewriting process happening behind the scenes. Automated Reasoning checks use logical deduction to automatically demonstrate that a statement is correct. Unlike large language models, Automated Reasoning tools are not guessing or predicting accuracy. Instead, they rely on mathematical proofs to verify compliance with policies. This blog post dives deeper into the implementation architecture for the Automated Reasoning checks rewriting chatbot.
Improve accuracy and transparency with Automated Reasoning checks
LLMs can sometimes generate responses…