1. A computer implemented system for managing power supply to an entire computer, comprising the following computer executable components: a learning component that is trained and constructs one or more probabilistic learning models according to usage patterns of the computer, wherein the one or more probabilistic models is a naive Bayesian model; a forecasting component that employs the learning component and the one or more probabilistic models to generate predictions relating to predicted usage of the entire computer, wherein the system assumes a variable T i for the i th time period and calculates P(T n+1 |T 1 ,T 2 ,. .. T n ) to compute usage probability; and a component that selects a power profile based at least in part upon the generated predictions relating to predicted usage of the entire computer and powers off, hibernates, or powers on the entire computer based at least in part on the selected power profile.