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Push Singh at PUSH 2005

Push Singh is interested in the hardest challenge of Artificial Intelligence, common sense. While programming a computer to beat humans at chess or index a million documents are solved problems, it’s still remarkably difficult to teach a computer than rain is wet and that humans don’t like to be wet.

At MIT’s Media Lab, Singh launched a project called OpenMind, which is a collaborative, participatory common sense knowledgebase for artificial intelligence. OpenMind now contains more than 750,000 “items” of knowledge – factual assertions – contributed by roughly 16,000 users. Users register to use the system and are presented with tasks that are comparatively simple for humans – writing a two-line description of a photo, adding five “facts” to explain a statement like “the boy drank the milk”.

The OpenMind system takes these user-contributed facts and uses them to build a set of tools – ConceptNet, LifeNet and StoryNet, each of which is an interconnected set of ideas that can help a computer solve common sense problems. ConceptNet links concepts together to help a computer understand what a natural language term means; StoryNet and LifeNet link situations together to let a program understand what events might lead to other events. Other tools include GlueNet, which help identify phrases that have similar meanings, and ShapeNet, a distributed approach to tuning computer vision.

OpenMind isn’t the only system attempting to solve problems like this using the agglomeration of common sense facts. Doug Lenat’s Cyc database has collected hundreds of thousands of “assertions” since the early 1980s; OpenCyc now is attempting to replicate some of this work in an open source environment. Singh describes OpenMind as being different in that it’s taking a wiki-like approach, noting that it was accepting user contributions before Wikipedia, in 2000.

(Push and I briefly talked about quality problems with user contributed material last night. He’s been pleasantly surprised at how little bogus data has been fed into the system. I’m wondering if this is because, unlike with Wikipedia, it’s very hard for anyone to see grafitti posted on the site. Your input goes into OpenMinds, but it’s hard to see where your input goes and what it does…)

As the database gets richer, it could be useful for building intelligent search engines, cameras that know when they should take a photo, or PDAs that know to cancel appointments when you’re out of town. I wish that Singh had a bit more time to show us some of the applications he and the Lab are using for the OpenMind database – it’s clear that this is a really interesting technique for assembling a body of common sense knowledge and less clear what this knowledge can eventually be used for.

7 thoughts on “Push Singh at PUSH 2005”

  1. Push isn’t making especially strong claims for the system – he seems to be more interested in collecting these inputs and in some of the social dynamics of collecting this information. I agree that the system looks a great deal like MindPixel – I’ll see if I can put that question to Push later today.

  2. work on openmind commonsense pre-dates, and far exceedes mindpixel in its contribution to ai. mindpixel was a stunt, at best, and had little to no grounding in previous commonsense reasoning work in ai. mindpixel was developed by someone more interested in recognition and fame than really solving the hard problems in ai. openmind commonsense catalyzed a movement in ai toward community collection and webmining of commonsense knowledge, techniques adapted now by cyc corp and other companies trying to crack problems of infering meaning from text.

  3. Openmind has been a great source of commonsense research and direction to any one who’s interested. With push passing away, I think its not much pursued by anyone coz most of openmind is now not functioning. But overall openmind has been a great source of inspiration to various commonsense projects like conceptnet, lifenet and storynet. I think openmind is a great way to collect commonsense info thru web mining making thousands of common pple to generated a commonsense knowledge base for research and development in Commonsense AI.


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