Bayesian learning systems are essentially another form of trainable neural network. That makes them very good in a narrow range of categories but also makes them insufficient to the cause of achieving general intelligence.

I do not see that scaling Bayesian learning networks would ever achieve general intelligence. No matter how big the hammer, it'll never be a wrench. That being said, I do believe that some form of pattern recognition and 'selective forgetting' is important to cognition and as such Bayesian learning architecture is a good tool towards that end.