I hate to make this discussion religious but NLU is widely used in industry to refer to systems such as ours. Daniel Jurafasky a professor at Stanford well known in industry uses NLU on page 822 chapter 24 of the book "Speech and Language Processing" to refer to a hypothetical frame and slot system very similar to what we have built. A quick search for Natural Language Understanding on google scholar will yield numerous articles which use NLU as a blanket term to refer to concepts in information extraction and NLP. Finally, SRI itself uses the term NLU to refer to these tasks (see: http://www.ai.sri.com/natural-language/projects/arpa-sls/ ). Hence I believe the terminology we used is in fact completely appropriate.
I'm excited to see someone talking about a single unified nexus for everything. That is part of the future vision of our company, and smart homes are an example of where we want to go in the next few years :)
Currently we support relative to the current time ("three hours from now") or absolute ("six pm"). We'd be happy to extend it however if we saw demand for extra functionality :) .
I feel that you have misunderstood what we have here. I agree that "true" understanding requires is almost an impossible problem to solve due to the fact that it requires context that is only available to the individual. However that level of understanding is not really necessary for applications today. What we are aiming to provide is a system that will allow developers to have natural language queries as their input and have all the pieces of information required for their application extracted. Secondly, the name "natural language understanding" is given to a large area of computer science ranging from sentiment analysis to information extraction. Many of the areas do not even involve deep understanding of contextual meaning in the way you describe. That however does not diminish the importance of any of these fields nor does it eliminate them from the the umbrella of natural language understanding.