[jpantony]

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.

[languagehacker]

You'd be a whole lot better of saying you've written a natural-language interface to a number of search domains. You're promising a lot by claiming to have an API that not only accomplishes understanding (which, contrary to your claim, is reserved for much deeper and more structured inferences than what you're providing here -- are you transforming sentences into a formal language before feeding it to epicurious, or are you just matching terms against a list of known food items?), but that it is accurate in its output. I still think that the claims of NLU are nothing short of hubris, and that the product would be more compelling if it didn't advertise something so unattainable.

[dgreensp]

I agree. I took the headline as a hypothetical question. The system described is the most pragmatic of natural language processing systems, a lovely term that just means the input is natural language and there is some processing.

I'm optimistic, by the way, and think that though "objective" word meaning is a cognitive illusion, we will crack the code within the next 20 years. But there is nothing on the forefront of that work about this system.

[jpantony]

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.

[languagehacker]

I appreciate your references, and I get where you're coming from, but that's not going to stop people from being disappointed by your claims. Just find a better name for it, and I'm sure people will like it more. The idea of being able to do voice recognition for something and being routed to one of many different domain-specific search engines is awesome, but it's a great example of the Searle's Chinese Room parable in practice. There's simply no understanding involved -- only heuristic.