Bayesian implementation concerns decision making problems when agents have incomplete information. This paper proposes that the traditional sufficient conditions for Bayesian implementation shall be amended by virtue of a quantum Bayesian mechanism. In addition, by using an algorithmic Bayesian mechanism, this amendment holds in the macro world. More importantly, we find that the revelation principle is not always right by using the quantum and algorithmic Bayesian mechanisms.