QuickAnswers Currently Limited but Possibly Promising

August 7, 2014

Sphere Engineering is looking to reinvent the way Web information is organized with QuickAnswers.io. This search engine returns succinct answers to questions instead of results lists. More a narrowed Wolfram|Alpha than a Google. At least that’s the idea. So far, though, it’s a great place to ask a question—as long as it’s a question to which the system knows the answer. I tried a few queries and got back almost as many “sorry, I don’t know”s or nonsense responses. For now, at least, the page admits that “the current state of this project only reflects a tiny fraction of what is possible.” Still, it may be worth checking back in as the system progresses.

The company’s blog post about the project lets us in on the vision of what QuickAnswers could become. Software engineer François Chollet writes:

“I recently completed a total rewrite of QuickAnswers.io, based on a new algorithm. I call it ‘shallow QA’, as opposed to IBM Waston’s ‘deep QA’. IBM Watson keeps a large knowledge model available for queries and thus requires a supercomputer to run. At the other end of the spectrum, QuickAnswers.io generates partial knowledge models on the fly and can run on a micro-instance.

“QuickAnswers.io is a semantic question answering engine, capable of providing quick answer snippets to any question that can be answered with knowledge found on the web. It’s like a specialized, quicker version of a search engine. You can see a quick overview of the previous version here.”

The description then gets technical. Chollet uses several examples to illustrate the algorithm’s approach, the results, and some of the challenges he’s faced. He also explains his ambitious long-range vision:

“In the longer term, I’d like to read the entirety of the web and build a complete semantic Bayesian map matching a maximum of knowledge items. Also, it would be nice to have access to a visualization tool for the different answers available and their frequency across sectors of opinion, thus solving the problem of subjectivity.”

These are some good ideas, but of course implementation is the tough part. We should keep an eye on these folks to see whether those ideas make it to fruition. While pursuing such visionary projects, Sphere Engineering earns its dough by building custom machine-learning and data-mining solutions.

Cynthia Murrell, August 07, 2014

Sponsored by ArnoldIT.com, developer of Augmentext

Comments

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