Curious to find out more, I emailed a former theoretical physicist who works (remotely) for Wolfram Research but sits just down the hall from me. Years ago I had lobbied for an office for him because, although he isn't primarily in physics research any more, he's a brilliant guy and was bound to end up doing something interesting. (Wanting to take advantage of the opportunity to work remotely at Wolfram he had researched the best places to live and ended up choosing Eugene.) Little did I know he's been leading the W|A project from here! He stumbled into my office yesterday to answer my questions and tell me that he's knee deep in reviewing code commits and getting ready for the launch :-)
My experience has confirmed over and over again that big brains tend to do interesting things. Whenever I meet someone who is "scary smart" (there are not so many in the world), I keep an eye out for what they do later in life.
Here is what AI researcher Doug Lenat wrote about W|A:
...At its heart is a formal Mathematica representation. Its inference engine is basically a large number of individually hand-engineered scripts for tapping into data which he and his team have spent the last several years gathering and "curating". For example, he has assembled tables of historical financial information about countries' GDP's and about companies' stock prices. In a small number of cases, he also connects via API to third party information, but mostly for realtime data such as a current stock price or current temperature. Rather than connecting to and relying on the current or future Semantic Web, Alpha computes its answers primarily from his own curated data to the extent possible; he sees Alpha as the home for almost all the information it needs, and will use to answer users' queries.
In an important sense, Alpha is a logical extension of Mathematica: it extends the range of types of information for which significant power can be gained by manually, and exhaustively, enumerating a large set of cases: airplane designs, cities, currencies, etc. I.e., Alpha extends what Mathematica has done previously for things like chemical compounds, geometric surfaces, topological configurations, arithmetic series, trigonometric ratios, and equations. In the new cases, as Mathematica did in those abstract math cases, Alpha excels at not just retrieving the stored data but performing various appropriate numeric calculations on the data, and displaying the results in beautiful graphs and easily comprehended tables for the user.
The resulting mosaic covers a large portion of the space of queries that the average person might genuinely want to ask, in the course of their day. The interface is not exactly natural language, but can be treated by the user as though it were -- just as users of browsers can treat them as though they parsed sentences even though they don't. A better way to think of it is a DWIMM ("do what I might mean"), so if you type in something like "gdp France / Germany", it calculates and returns a graph of the relative fraction of France's annual GDP to Germany's GDP, over the last 30 years or so. If you just type in "gdp", it looks up your local host and (in my case) displays the GDP of the USA over the last 30 years, plus various pieces of information about what gross domestic product is, from a mathematical formula perspective but not from a semantic one. It does not have an ontology, so what it knows about, say, GDP, or population, or stock price, is no more nor less than the equations that involve that term.
See also this video of a lecture by Wolfram about W|A.