kef writes:
"By 2029, computers will be able to understand our language, learn from experience and outsmart even the most intelligent humans, according to Google's director of engineering Ray Kurzweil.
Kurzweil says:
Computers are on the threshold of reading and understanding the semantic content of a language, but not quite at human levels. But since they can read a million times more material than humans they can make up for that with quantity. So IBM's Watson is a pretty weak reader on each page, but it read the 200m pages of Wikipedia. And basically what I'm doing at Google is to try to go beyond what Watson could do. To do it at Google scale. Which is to say to have the computer read tens of billions of pages. Watson doesn't understand the implications of what it's reading. It's doing a sort of pattern matching. It doesn't understand that if John sold his red Volvo to Mary that involves a transaction or possession and ownership being transferred. It doesn't understand that kind of information and so we are going to actually encode that, really try to teach it to understand the meaning of what these documents are saying.
Skynet anyone?"
(Score: 5, Insightful) by buswolley on Monday February 24 2014, @02:51AM
http://www.scholarpedia.org/article/Models_of_hipp ocampus [scholarpedia.org]
One region of the brain that has attracted a great deal of attention in the computational modeling literature is the hippocampus. several reason that the hippocampus has received so much attention by modelers is 1) the importance of this region to memory 2)the great neuroscience knowledge that has been acquired on this brain region, and 3) the elegant structure the subfields of the hippocampus.
subicular junctures