Through this Bayesian method, you could imagine learning any problem as long as you had a starting probability and enough cycles to update the probabilities. Similarly, a computer could solve any problem if it had a prior probability and enough data and compute power to continually adjust that probability—in other words, error correction and refinement of hypothesis through iterations. Intelligence.
