A small, trusted kernel: a few thousand lines of code that check every step of every proof mechanically. Everything else (the AI, the automation, the human guidance) is outside the trust boundary. Independent reimplementations of that kernel, in different languages (Lean, Rust), serve as cross-checks. You do not need to trust a complex AI or solver; you verify the proof independently with a kernel small enough to audit completely. The verification layer must be separate from the AI that generates the code. In a world where AI writes critical software, the verifier is the last line of defense. If the same vendor provides both the AI and the verification, there is a conflict of interest. Independent verification is not a philosophical preference. It is a security architecture requirement. The platform must be open source and controlled by no single vendor.
fn unwrap_or_self(&self) - &Self::Inner;
，这一点在PDF资料中也有详细论述
In this paper, we present a new framework for understanding AI’s labor market impacts, and test it against early data, finding limited evidence that AI has affected employment to date. Our goal is to establish an approach for measuring how AI is affecting employment, and to revisit these analyses periodically. This approach won't capture every channel through which AI could reshape the labor market, but by laying this groundwork now, before meaningful effects have emerged, we hope future findings will more reliably identify economic disruption than post-hoc analyses.，详情可参考WPS下载最新地址
В Израиле одним словом оценили ход операции против Ирана14:58
同一个 channel ID 只保留优先级最高的版本，避免冲突。