Wolfram|Alpha - Not exactly how we typically think about search, but very cool
We find it difficult to describe what Wolfram|Alpha is and where the discussion of this service should fit within our content. Is it search, simulation, productivity tool, or what? On the surface, it looks very much like a search service. There is the familiar box for entering queries, but you soon discover by entering traditional search requests that this service is different. Many of us explore search services by doing what is sometimes called a vanity search; we search for our name. Try this with Wolfram|Alpha and you likely are told "Wolfram|Alpha doesn't know how to interpret your input".
Maybe we should back up and try to understand search and discovery on a more general level. What are we seeking and what form do we expect this information to take? We have grown to expect online search to locate useful information which, when you think about it, is often just the beginning of the process. Unless we are asking a basic, factual question, the information we locate must still be examined and interpreted. We are searching for content we then explore. Wolfram|Alpha does return information, but it also tries to answer certain categories of questions. These questions tend to involve mathematics.
In attempting to differentiate Wolfram|Alpha from search services, their site describes Wolfram as a computational knowledge engine. We would describe it as the combination of a natural language processor to interpret your query, databases of information, and computational power. The natural language processor attempts to interpret what you want and uses this interpretation to search the databases to locate information relevant to your request. It is not like talking with another person, but you do get the hang of how the service wants queries to be phrased after trying the service for a while or examining a list of typical queries the service provides. The system is capable of performing calculations on the numerical data it locates (or you provide). Your request can be capricious - [height of mount everest - height of empire state building]. The response was 27,785 feet and was explained as Mount Everest elevation - 29,035 feet and height - Empire State Building - 1250 feet.
Remember the spreadsheet activity we proposed in Chapter 3 to solve the equation. Submit the equation 4x-14=4-2x to Wolfram|Alpha and it returns the following:
You will see the solution (X=3), a graph nearly identical to the graph we had the spreadsheet construct, and alternate forms for the equation [6x-18=0, 2(2x-7)=-2(x-2)].
This is actually pretty basic stuff, Wolfram|Alpha is built on top of the powerful mathematical capabilities of Mathematica, the tool used by scientists and in many college mathematics and sciences courses.
Conrad Wolfram, developer of Mathematica and online entrepreneur responsible for Wolfram|Alpha, has a broad perspective that we interpret as mathematical problem solving. He sees math problems everywhere and also feels our present focus in math education is off the mark. According to Wolfram we have become stuck on calculation (he claims we spend 80% of our instructional time focused on calculation) and this is the part of applying math that machines do best. By focusing on calculation we make math uninteresting and possibly even more difficult in that challenges are disconnected from a meaningful context. We might suggest that he sees Wolfram|Alpha as a way to “scaffold” mathematical problem solving. It allows us to take on more interesting and challenging problems with support. Wolfram shares his perspective in a recent Ted Talk (Teaching Kids Real Math With Computers).
Perhaps the best way to explore Wolfram|Alpha is to explore the examples the site provides. We list several resources at the end of this section.
Resources:
Conrad Wolfram Ted talk on math education