For the last 10 months, Carnegie Mellon University’s Never-Ending Language Learning System, or NELL, has been continuously searching the web for text patterns and grouping them into different semantic categories, a system that closely mimics the way humans learn. But NELL has adopted another human behavior as well: tweeting everything she does.
When she learns a new fact, NELL adds it to her online database, and tweets her discoveries, so you can follow her progress. For example, today she learned that the phrase “dem franchise boys” fits in the category of “music artist.” NELL’s knowledge base currently consists of around 440,000 facts, with around 87 percent accuracy. Many of her tweeted lessons demonstrate amazing analytical capabilities - she was able to get “tool” from “Anchor Fixing Self Tapping Screw Bolts.” The New York Times recently published an in-depth look at exactly how NELL learns these things.
NELL isn’t perfect though. And thank goodness, because that means we get some pretty adorable not-quite-there-yet tweets, such as: “I think “chicken recipe time” is a #condiment” and “I think “anonymously” is a #fish.” NELL’s followers can tweet corrections to her and help her improve her associations. Check out her feed or browse her whole knowledge database to see more.
Well if 440,000 facts arent enough to make a computer smart, i dont know what is.
Could it be a sensible pointless system….
Sensible because each AI system would need to make such system, and pointless because every AI system would need to make such a system….
For one thing i dont think facts are stored in such a meticulous fashion in us. But on another note if i were creating a system that was better than our intelligence I might enjoy a preprepared database of accurate facts.