Using neural-net programming to crack languages fast.

FROM UZBEK TO KLINGON, THE MACHINE CRACKS THE CODE

Statistical machine translation - in which computers essentially learn new languages on their own instead of being "taught" the languages by bilingual human programmers - has taken off. The new technology allows scientists to develop machine translation systems for a wide number of obscure languages at a pace that experts once thought impossible.

Dr. Knight and others said the progress and accuracy of statistical machine translation had recently surpassed that of the traditional machine translation programs used by Web sites like Yahoo and BabelFish. In the past, such programs were able to compile extensive databanks of foreign languages that allowed them to outperform statistics-based systems.

Traditional machine translation relies on painstaking efforts by bilingual programmers to enter the vast wealth of information on vocabulary and syntax that the computer needs to translate one language into another. But in the early 1990's, a team of researchers at I.B.M. devised another way to do things: feeding a computer an English text and its translation in a different language. The computer then uses statistical analysis to "learn" the second language.

The original NYTimes article looks pay only now.

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This is really neural-net learning. If I was still at Quest I might have had the opportunity to use neural-net software for marketuing research studies. Right now I use it in a game I am playing. The computer learns from previous moves what things are more likely to work in what circumstances. In fact, it is released with the code from analyzing 140 automated player's actions for 100 turns in 100 games. It was advised if possible to run the learning program on your machine but it would take weeks to complete and takes over the entire machine.