I just saw an interesting talk from the 2010 singularity summit by demis Hassabis. He spoke about the failings of traditional ai, one of which is that it ignored for decades the only known example of high-level intelligence (the human brain). At the other end of the spectrum, he mentioned the brain simulation projects such as blue brain and darpa synapse, which tend to understand the wiring of the brain, but not its functions. Hassabis argued for a middle ground approach that combines the best of machine learning and neuroscience, which of course is the approach being taken by Numenta.
Hassabis mentioned that brain-inspired deep learning approaches such as htm and deep belief nets have made significant progress. He made the interesting point that these systems are becoming good at sensory perception, but that as of yet, it is not known how we can create the brain's conceptual knowledge from sensory knowledge. Hassabis clearly believes that something like htm cannot alone produce abstract knowledge. I personally am not convinced that sensory knowledge can't lead to abstract knowledge. The fact of the matter is that everything we know is derived from our sensory experiences, past and present. I am not naive enough to think that HTM theory is a comprehensive explanation of brain function. It just seems to me that sensory data could over time produce increasingly abstract knowledge. The whole idea of a hierarchy of space and time is that successively higher layers of the hierarchy contain increasingly invariant, abstract representations, so I don't see even see a clear difference between perceptual and abstract knowledge. Our ideas about love, hate, and anger all arise from past and present sensory experiences, from seeing, hearing, touching, and otherwise experiencing the good and bad of humanity, learning to represent in our minds these abstract ideas.