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You are here: Home / Business Briefing / Wolfram Knowledge Engine Launches
Wolfram Knowledge Engine Begins Computing Answers
Wolfram Knowledge Engine Begins Computing Answers
By Barry Levine / CRM Daily Like this on Facebook Tweet this Link thison Linkedin Link this on Google Plus
The world's information may be more digestible, following the launch over the weekend of Wolfram Alpha, the "computational knowledge engine" from Wolfram Research.

"Our goal," read a statement on the Web site, "is to build on the achievements of science and other systematizations of knowledge to provide a single source that can be relied on." A search-engine interface enables the user to use "free-form input" -- that is, natural-language queries -- to search expert-level knowledge and to compute "whatever can be computed about anything."

10,000 Messages Over the Weekend

The engine was built by Wolfram Research, the Illinois-based company of scientist Stephen Wolfram, whose best-known products include the Mathematica software tool and A New Kind of Science, a best-selling book and approach to scientific problems using a set of basic formulas.

On its company blog, Wolfram Alpha said it received almost 10,000 messages over its launch weekend from feedback forms. Many were comments about other information that needed to be added to answers. For instance, one poster had input just "piano," and complained that it only returned characters from the movie, The Piano. The Wolfram Alpha team responded that it intends to add musical instruments.

Praise around the Web for the computational engine has been strong, but there were also some complaints. Some have said the tool doesn't follow Web-standard accessibility guidelines, and others have noted that a number of inquiries resulted in the engine saying it didn't understand the question, or that the process by which an answer was "curated" is too obscure.

Wolfram Alpha contains more than 10 trillion pieces of data, as well as 50,000 types of algorithms and models. The engine was built using Mathematica, consists of more than five million lines of code, and runs on supercomputer-class clusters. The knowledge base, according to news reports, is being built by a Wolfram Research team of about 100 people.

'Am I Too Drunk to Drive?'

In one example given on the site, a user asks, "Am I too drunk to drive?" The results show the number of drinks (two) for a 140-pound male over an hour, the estimated blood-alcohol percentage (0.06 percent), and the legal driving limit in the U.S. (0.08 percent). It also shows a graph of blood alcohol over time.

Ask "What is the temperature in Boston?" and it shows not only the current temperature in Fahrenheit, but a chart of temperatures over selectable time spans, as well as comparisons from several media outlets in the metropolitan area that are sorted by "distance and inferred reliability."

Wolfram has said that current search engines are efficient in answering questions that have been asked before, because they retrieve existing knowledge. But how do you ask a question about something that hasn't been answered before? One way to do that, according to Wolfram, could be the emerging semantic Web, where information is tagged as to its meaning. But another way, the approach taken in Wolfram Alpha, is using algorithms to "explicitly curate all data so that it is immediately computable."

Some observers have suggested the engine might be readying itself to take on industry search leader Google. If so, this kind of approach to knowledge queries would need to be attractive to advertisers.

Andrew Frank, an analyst with industry research firm Gartner, said Wolfram Alpha might "represent a deeper and narrower targeting opportunity for certain kinds of contextual marketing," and it could "earn a share of search revenue," especially for advertising related to technical research.

But, he said, he doesn't see Wolfram Alpha threatening Google in the consumer or general-business market. In fact, he pointed out, Google's AdSense ads might work well for Wolfram Alpha.

Image credit: iStock.

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