Wolfram|Alpha

I spent a few minutes playing with Wolfram|Alpha today, its first full day of public availability. While the launch of this service was very recent, Wolfram|Alpha has a longer history than you might think. It’s built off of Mathematica, which I never used as a student but I certainly heard about from my math-loving friends. Mathematica was released over 20 years ago and named by Steve Jobs.

At first glance, Wolfram|Alpha looks like a traditional search engine, but it’s different than the types of search engines you’re used to associating with a web service.

It strives to provide answers to factual queries based on data visualization and computation. Yeah, I don’t think I explained it well either. Let’s just jump to some sample queries to show what I mean. I’m pretty bad at calculating time, so let’s have computers tell me the answers:

How much longer until my birthday? (my first query!)
[days until dec 31, 2009]

How much time do I have to ride my bike? I don’t have a bike light.
[time until sunset] or just [sunset]

When is this 87-minute movie going to be over if I start watching at 7:15?
[7:15 + 87 minutes]

Here’s the first query I tried which didn’t work. I wanted to see if I could add up times (in MM:SS format) to see how much video I’ve uploaded to YouTube. I put in these sample values:
[4:15 + 2:10 + 18:37]

Bummer. But with a little bit of find/replace I could get an input that Wolfram|Alpha understood:
[4 minutes 15 seconds + 2 minutes 10 seconds + 18 minutes 37 seconds]

I entered all of those queries with limited knowledge about what types of questions Wolfram|Alpha could answer, and had no idea what a correct syntax should look like. Fortunately, it does a pretty good idea of understanding what I’m trying to ask, which is what’s expected of search engines today. After I played around with time-based computation, I tried a couple of other queries:

[population of doylestown, pa and population of sunnyvale, ca]

This one did not work:
[populations of doylestown, pa and sunnyvale, ca in 1983]

Here’s a fun one that I originally learned from Google’s calculator:
[number of horns on a unicorn]

And this one from Monty Python:
[velocity of an unladen swallow]

As you can see, the results are better when you’re more specific:
[velocity of an unladen european swallow]

Those should be enough to get you started, but if you need more inspiration or are looking for more diverse examples, check out this list.