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I think, therefore I'm a computer?
Researchers in US aim to program computers to use common sense
PITTSBURGH - Researchers are trying to plant a digital seed for artificial intelligence by letting a massive computer system browse millions of pictures and decide for itself what they all mean.
The system at Carnegie Mellon University is called Neil, short for Never Ending Image Learning. In mid-July, it began seraching the Internet for images 24/7 and, in tiny steps, is deciding for itself how those images relate to each other.
The goal is to recreate what we call common sense - the ability to learn things without being specifically taught.
It is a new approach in the quest to solve computing's Holy Grail: getting a machine to think on its own using a form of common sense. The project is being funded by Google and the US Department of Defence's Office of Naval Research.
"Any intelligent being needs to have common sense to make decisions," said Professor Abhinav Gupta of Carnegie Mellon's Robotics Institute.
Neil uses advances in computer vision to analyse and identify the shapes and colours in pictures, but it is also slowly discovering connections between objects on its own. For example, the computers have figured out that zebras tend to be found in savannahs and that tigers look somewhat like zebras.
In just over four months, the network of 200 processors has identified 1,500 objects and 1,200 scenes and has connected the dots to make 2,500 associastions.
Some of Neil's computer-generated links are wrong, such as "rhino can be a kind of antelope", while some are odd, such as "news anchor can look similar to Barack Obama", Prof Gupta said having a computer make its own associations is an entirely different type of challenge than programming a supercomputer to do one thing very well, or fast.
For example, in 1985, Carnegie Mellon researchers programmed a computer to play chess; 12 years later, a computer beat world chess champion Garry Kasparov in a match.
Dr Robert Sloan, an expert on artificial intelligence and head of the computer science department at the University of Illinois, Chicago, said the Neil approach could yield interesting results because just using language to teach a computer "has all sorts of problems unto itself".
"What I would be especially impressed by is if [the computers] can consistently say 'zebra, zebra, zebra' if they see the animal in different locations," he said.
In the future, Neil will analyse vast numbers of YouTube videos to look for links between objects.
Neither Google nor the Office of Naval Research Research responded to queries about why they are funding Neil, but there are hints.
The Naval Research website notes "today's battlespace environment is much more complex than in the past" and "the rate of which data is arriving into the decision-making system is growing, while the number of humans available to convert the data to actionable intelligence is decreasing". In other words, computers may make some of the decisions in future wars.
ASSOCIATED PRESS
Researchers in US aim to program computers to use common sense
PITTSBURGH - Researchers are trying to plant a digital seed for artificial intelligence by letting a massive computer system browse millions of pictures and decide for itself what they all mean.
The system at Carnegie Mellon University is called Neil, short for Never Ending Image Learning. In mid-July, it began seraching the Internet for images 24/7 and, in tiny steps, is deciding for itself how those images relate to each other.
The goal is to recreate what we call common sense - the ability to learn things without being specifically taught.
It is a new approach in the quest to solve computing's Holy Grail: getting a machine to think on its own using a form of common sense. The project is being funded by Google and the US Department of Defence's Office of Naval Research.
"Any intelligent being needs to have common sense to make decisions," said Professor Abhinav Gupta of Carnegie Mellon's Robotics Institute.
Neil uses advances in computer vision to analyse and identify the shapes and colours in pictures, but it is also slowly discovering connections between objects on its own. For example, the computers have figured out that zebras tend to be found in savannahs and that tigers look somewhat like zebras.
In just over four months, the network of 200 processors has identified 1,500 objects and 1,200 scenes and has connected the dots to make 2,500 associastions.
Some of Neil's computer-generated links are wrong, such as "rhino can be a kind of antelope", while some are odd, such as "news anchor can look similar to Barack Obama", Prof Gupta said having a computer make its own associations is an entirely different type of challenge than programming a supercomputer to do one thing very well, or fast.
For example, in 1985, Carnegie Mellon researchers programmed a computer to play chess; 12 years later, a computer beat world chess champion Garry Kasparov in a match.
Dr Robert Sloan, an expert on artificial intelligence and head of the computer science department at the University of Illinois, Chicago, said the Neil approach could yield interesting results because just using language to teach a computer "has all sorts of problems unto itself".
"What I would be especially impressed by is if [the computers] can consistently say 'zebra, zebra, zebra' if they see the animal in different locations," he said.
In the future, Neil will analyse vast numbers of YouTube videos to look for links between objects.
Neither Google nor the Office of Naval Research Research responded to queries about why they are funding Neil, but there are hints.
The Naval Research website notes "today's battlespace environment is much more complex than in the past" and "the rate of which data is arriving into the decision-making system is growing, while the number of humans available to convert the data to actionable intelligence is decreasing". In other words, computers may make some of the decisions in future wars.
ASSOCIATED PRESS
