David Weinberger and Nova Spivack Are Both Taking This Seriously …

… and so I shall also.

I am referring to the Wolfram Alpha … David mentions it here, noting that Stephen Wolfram is “very very very very very smart”.  Coming from David, that is an automatic signal to pay attention.

Following the link in a tweet from Tim O’Reilly, I see that Nova Spivack, founder of Radar Networks and Twine, is also very interested (excerpt below).  Another strong early signal …

Now I am interested, and I will follow the developments.

 

Stephen Wolfram is building something new — and it is really impressive and significant. In fact it may be as important for the Web (and the world) as Google, but for a different purpose.

Stephen was kind enough to spend two hours with me last week to demo his new online service — Wolfram Alpha (scheduled to open in May). In the course of our conversation we took a close look at Wolfram Alpha’s capabilities, discussed where it might go, and what it means for the Web, and even the Semantic Web.

Stephen has not released many details of his project publicly yet, so I will respect that and not give a visual description of exactly what I saw. However, he has revealed it a bit in a recent article, and so below I will give my reactions to what I saw and what I think it means. And from that you should be able to get at least some idea of the power of this new system.

A Computational Knowledge Engine for the Web

In a nutshell, Wolfram and his team have built what he calls a “computational knowledge engine” for the Web. OK, so what does that really mean? Basically it means that you can ask it factual questions and it computes answers for you.

It doesn’t simply return documents that (might) contain the answers, like Google does, and it isn’t just a giant database of knowledge, like the Wikipedia. It doesn’t simply parse natural language and then use that to retrieve documents, like Powerset, for example.

Instead, Wolfram Alpha actually computes the answers to a wide range of questions — like questions that have factual answers such as “What hemisphere is Timbuktu in?” or “How many protons are in a hydrogen atom?” or “What was the average rainfall in Seattle last month?,” “What is the 300th digit of Pi?,” “where is the ISS?” or “When was GOOG worth more than $300?”

Think about that for a minute. It computes the answers.

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