Another Word For It Patrick Durusau on Topic Maps and Semantic Diversity

November 27, 2011

Siri’s Sibling Launches Intelligent Discovery Engine

Filed under: Agents,Artificial Intelligence,Search Engines,Searching — Patrick Durusau @ 8:56 pm

Siri’s Sibling Launches Intelligent Discovery Engine

Completely unintentional but I ran across this article that concerns Siri as well:

We’re all familiar with the standard search engines such as Google and Yahoo, but there is a new technology on the scene that does more than just search the web – it discovers it.

Trapit, which is a personalized discovery engine for the web that’s powered by the same artificial intelligence technology behind Apple’s Siri, launched its public beta last week. Just like Siri, Trapit is a product of the $200 million CALO Project (Cognitive Assistant that Learns and Organizes), which was the largest artificial intelligence project in U.S. history, according to Mashable. This million-dollar project was funded by DARPA (Defense Advanced Research Projects Agency), the Department of Defense’s research arm.

Trapit, which was first unveiled in June, is a system that personalizes content for its users based on keywords, URLs and reading habits. This service, which can identify related content based on contextual data from more than 50,000 sources, provides a simple, carefree way to discover news articles, images, videos and other content on specific topics.

So, I put in keywords and Trapit uses those to return content to me, which if I then “trapit,” the system will continue to hunt for related content. Yawn. Stop me if you have heard this story before.

Keywords? That’s what we get from “…the largest artificial intelligence project in U.S. history?”

From Wikipedia on CALO:

Its five-year contract brought together 300+ researchers from 25 of the top university and commercial research institutions, with the goal of building a new generation of cognitive assistants that can reason, learn from experience, be told what to do, explain what they are doing, reflect on their experience, and respond robustly to surprise.

And we got keywords. Which Trapit uses to feed back similar content to us. I don’t need similar content, I need content that doesn’t use my keywords and yet is relevant to my query.

But rather than complain, why not build a topic map system based upon “…cognitive assistants that can reason, learn from experience, be told what to do, explain what they are doing, reflect on their experience, and respond robustly to surprise.” Err. that would be crowdsourcing topic map authoring, yes?

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