It has seemed to me, for a very long time, that modern AI systems would need to be integrated with standard RDBMS systems for reliable persistant storage of raw information, some sort of no-sql database (memcache or some variant) for persistant storage of associations, some sort of document database for blocks of textual information, a SPARQL system for searching semantically-marked information within the document database, and a more old-fashioned back-propogation NN to provide a store of understanding that the user can directly manipulate.
Probabalistic classifiers are all fine and good, but only for a subset of the tasks needed. The above structure is a very loose, wildly-speculative initial framework. It's almost certain that if you actually tried building an integrated multi-model system, that you'd end up making a lot of changes to this basic idea, but that you'd end up having to implement the same core concepts that are identified in it.