ÑóẊîöʼn
21st February 2011, 08:52
The Register.co.uk (http://www.theregister.co.uk/2011/02/19/ibm_watson_is_not_a_supercomputer/)
The second part of the article is of particular interest:
No supercomputer required
What is coming across in the media, fortunately, is why all of this matters: real-time answers that are accurate despite the human frailty of the information we provide and the questions we ask. We human types are ambiguous. We have nearly endless ways to say the same thing. Our statements and questions are unstructured, and must be interpreted through the context in which they’re made.
Computers want things to be black or white. They have to go to great lengths (as we can see above) to be able to figure out the meanings in human statements or questions. Humans are great at processing ambiguous, unstructured data; our brains are wired to see patterns and put together theories as to why those patterns occur. Computers are great at doing the grunt work of sifting through masses of evidence to either support or disprove our theories.
This Jeopardy exercise isn’t about computers besting humans. It’s really about how collections of computing hardware and software can be optimized to understand humans better, and to understand what we’re trying to get them to do. A lot of time, effort, and money is expended in getting real-world data into a form where it can be understood and processed by digital devices like computers. Watson is the best recent example of a machine crossing over the divide between human and machine-style thinking.
This means that in the future, we’ll be able to spend more time on actual human work and less time on generating digital-compatible data to feed the machines. This will pay concrete dividends even in the near term. Information from thousands of patients’ vital signs and millions of clinical reports and doctors’ notes could be synthesized to provide diagnoses that aren’t guesswork.
Businesses can make sense of staggering amounts of data that have been “noise” until now. Who knows – maybe our consumer information and requests and incoherent rants could be analyzed in such a way that we get actual help from a help desk. No supercomputer required. ®
One of the major challenges of Artificial Intelligence is dealing with ambiguity. Machines like Watson show us how far we've come and where we may be heading.
The second part of the article is of particular interest:
No supercomputer required
What is coming across in the media, fortunately, is why all of this matters: real-time answers that are accurate despite the human frailty of the information we provide and the questions we ask. We human types are ambiguous. We have nearly endless ways to say the same thing. Our statements and questions are unstructured, and must be interpreted through the context in which they’re made.
Computers want things to be black or white. They have to go to great lengths (as we can see above) to be able to figure out the meanings in human statements or questions. Humans are great at processing ambiguous, unstructured data; our brains are wired to see patterns and put together theories as to why those patterns occur. Computers are great at doing the grunt work of sifting through masses of evidence to either support or disprove our theories.
This Jeopardy exercise isn’t about computers besting humans. It’s really about how collections of computing hardware and software can be optimized to understand humans better, and to understand what we’re trying to get them to do. A lot of time, effort, and money is expended in getting real-world data into a form where it can be understood and processed by digital devices like computers. Watson is the best recent example of a machine crossing over the divide between human and machine-style thinking.
This means that in the future, we’ll be able to spend more time on actual human work and less time on generating digital-compatible data to feed the machines. This will pay concrete dividends even in the near term. Information from thousands of patients’ vital signs and millions of clinical reports and doctors’ notes could be synthesized to provide diagnoses that aren’t guesswork.
Businesses can make sense of staggering amounts of data that have been “noise” until now. Who knows – maybe our consumer information and requests and incoherent rants could be analyzed in such a way that we get actual help from a help desk. No supercomputer required. ®
One of the major challenges of Artificial Intelligence is dealing with ambiguity. Machines like Watson show us how far we've come and where we may be heading.