A computer at Carnegie Mellon University has been reading the internet for the past 10 months, spotting patterns in language and sorting things into categories. It knows Peyton Manning is a football player and the Indianapolis Colts is a football team, for example. It can go one further and estimate that Manning plays for the Colts and tell you how certain it is of that connection.
The Never-Ending Language Learning system, or NELL, has made an impressive showing so far. NELL scans hundreds of millions of Web pages for text patterns that it uses to learn facts, 390,000 to date, with an estimated accuracy of 87 percent. These facts are grouped into semantic categories — cities, companies, sports teams, actors, universities, plants and 274 others. The category facts are things like “San Francisco is a city” and “sunflower is a plant.” [NewYorkTimes]
The technology holds great potential: search results as a written reply instead of just links, computerized personal assistants that respond to questions, and other important things I can’t be arsed to look up. I tried to reach this fancypants computer to get a comment, but he called me a n00b and told me “T*ts or GTFO”. Hey, you’re only ten months old, mister. Don’t think I won’t wash your ports out with soap.
Naw, just kidding. NELL didn’t say that, and she’s not even a he. What she said was, “Tay ina win.”
Tay ina win.