I am 100% convinced the way forward in AI is finding the right data structure(s) that allows us to bridge between rigorous but inflexible symbolic algebras and dynamic/fluid but blurry probabilistic networks (like DLs).
One thing that I find of concern is that maybe the right way to do it implies building a network that builds the sylbolic algebra itself like suggested in the article. I feel that this approach would require tremendous amount of computation to yield results, much like the genetic code that makes our brain required hundreds of millions of years of trials and errors accross trillions of creatures around the whole planet to get to where it is now.
Maybe there are ways to short circuit this costly evolutionary process. But I cannot think of a simple, elegant one.