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A new search service that brings a measure of artificial intelligence to traditional Internet searching is set to go public soon. Wolfram|Alpha has been anticipated for several months, and the company behind it recently drew attention by opening access to a small number of testers.
The service should launch late this week, states the company's blog, though it names May 18 as the official date.
The brainchild of creator Stephen Wolfram, Wolfram|Alpha is a computational knowledge engine that analyzes the relationships among search terms to create an answer to a search query. It is based on Wolfram's math formula software Mathematica, a tool for scientific computation that also functions as a programming language.
Wolfram Research, the company Wolfram created, has been providing selective access to testers in preparation for the planned launch.
The Wolfram search engine is not likely to go into head-to-head competition with the likes of Google (Nasdaq: GOOG), Yahoo (Nasdaq: YHOO) or Microsoft (Nasdaq: MSFT) Live Search. Instead, it will provide researchers with an alternative approach to traditional searching.
"What they are doing is brilliant. This will shorten people's work time. It is a great boon for productivity," Brooke Aker, CEO of semantic search technology firm Expert Systems, told TechNewsWorld.
What It Does
Wolfram|Alpha is not a traditional search engine that plows through Web pages based on keywords. Instead, it computes a response based on the data contained in the company's own knowledge database in conjunction with an artificial intelligence system.
What sets Wolfram|Alpha apart from other search engines is its ability to do sophisticated pure computations involving numbers or formulas users enter. These computations are applied automatically to data called up from its repositories. Computation is what turns generic information into specific answers, Wolfram wrote in a May 1 blog entry.
Traditional search engines like Google and Yahoo crawl the Internet with spider programs to present a catalog of Web site content. Wolfram|Alpha, on the other hand, attempts to answer natural language questions, explained Scott Testa, professor of marketing at St. Joseph's University.
"This takes semantic search to the next level. Natural language search ... is the Holy Grail of the industry," Testa told TechNewsWorld.
Problem Solver
Wolfram/Alpha addresses a longstanding dilemma.
Search engines answer questions differently than people do in conversations, according to Nathan Myhrvold, founder and CEO of invention firm Intellectual Ventures. Myhrvold was a key player in founding Microsoft Research and numerous technology groups associated with some of Microsoft's most successful products.
"Stephen has developed a system that answers natural language questions. This is definitely brand new technology. People have been trying natural language searches for a long time," Myhrvold told TechNewsWorld.
The computer has to understand what the person making the query means, not just what the words mean, he added.
Different Approach
Wolfram|Alpha goes beyond common semantic search techniques. Most semantic search engines attempt to interpret the search terms, but Wolfram's method takes the concept to a new level, according to Aker.
"I think the tools we have now don't go far enough," he said.
One example Wolfram offered in his blog: a computational search focused on finding the number of calories in a recipe. The basic data involves the calories per gram of each of the ingredients. However, turning that generic information into the actual total calories for a specific recipe requires computation, he wrote.
For instance, unit conversions of so many cups into grams of flour and the default weight of a standard egg have to be computed to multiply the calories per ingredient and then totaled.
Mathematica Basics
The math formula system Wolfram developed over the last 20 years is the foundation of his new search engine. Mathematica's symbolic language lets searchers express complex computational processes in a fluid, intuitive way. Users do not have to toil with what he called "the ugly details of data structures, memory allocation, or confusing and inconsistent subroutine libraries."
The symbolic nature of the Mathematica language makes possible a great degree of interoperability between different parts of the system and between different algorithms and data sources. It represents all kinds of data with arbitrarily structured symbolic expressions, according to Wolfram.
The combination of Mathematica and the use of the highly specialized database are what make Wolfram|Alpha so unique, said Testa.
"Every 12 to 18 months, a new attempt surfaces to beat Google. Most fade away. Wolfram is playing it low-key ... . My gut is that his existing reputation is going to make sure that this is something pretty significant," he predicted.
Unanswered Questions
The real significance of Wolfram's new technology is the impact it will have on the targeted users. This certain user class can get exact answers. It is a more efficient allocation of resources, said Expert Systems' Aker.
However, Wolfram Research so far has not spelled out exactly who those users are and how much, if anything, the service will cost. For instance, general users may be provided with limited access for free. Professional users might be offered more features for a subscription.
Another unanswered question is whether the company's proprietary database is robust enough. In all likelihood, some questions posed in the search window will come back blank if there is not enough data compiled.
"Lycos, the first Internet search engine, was awful when it started. Even Google was not as good when it started as it is today," Intellectual Ventures' Myhrvold pointed out. Wolfram|Alpha will find stuff that you could never find with Google today. I think people will be excited about the launch and will find Alpha useful. It will have the potential for some users to become frustrated."
Too Limited?
Some criticism of Wolfram's approach could focus on the end-user application of these search concepts and tools. Key areas of focus for the search engine include Machine Learning, Semantics/Natural Language Processing (NLP) and Common Sense Reasoning. The key is to proactively bring the content that matters most to the user, as well as connect them with others who are looking for the same thing, according to Jim Anderson, CTO of Saber Seven.
Saber Seven is developing a solution that brings the answers to the user and refines the process with all these techniques integrated into the experience.
"Wolfram Alpha might be helpful for confined, factual questions like
'What type of metal is the Liberty Bell made of?'" Anderson told TechNewsWorld. "However, these
simple and very specific questions don't address the real, complex
questions people are looking for, like 'I'm writing a paper on
freedom. Where do I start?'"
