Burhan(TruthCert)fail-closed verification LLM outputs(measure false-ship rate) (github.com)

TruthCert has announced a new certification protocol designed to ensure the reliability of outputs generated by large language models (LLMs) in high-stakes environments, such as evidence extraction and research. Unlike traditional models, TruthCert is a fail-closed verification and disclosure standard that allows outputs to "ship" only if they adhere to a specified policy and can be audited. This is crucial in preventing quietly erroneous outputs that may appear confident but lead to significant issues, such as incorrect conclusions or misrepresentations. The core functionality of TruthCert centers on certified outputs that are scope-locked, include detailed provenance for every atomic value, and require validation from multiple independent witnesses. Notably, the protocol mandates the rejection of any output that does not meet its stringent verification criteria, ensuring that all released information is rigorously checked. This initiative represents a significant advancement in the AI/ML community, as it establishes a framework for accountability and trustworthiness in AI-generated content, thus addressing one of the field's major concerns: ensuring high-integrity outputs in critical applications.