As a non-techie, I don't understand the language example they're using. It seems to me many prediction engines are originally built to try to forecast winning lottery numbers or other such gambling events. Google expects me to believe they did this for language?
The point is that they took a large number of documents, which are clearly labelled as to language, gave it as a training set to the machine, and they now have a classifier that lets you input random text and tells you the language it was probably written in.
In principle you can do this with any data set and any set of discrete outcomes.
In general, though, you should expect that the resulting classifier won't give you much insight on why it came up with the answers that it did. Plus it frequently is less accurate than a trained human. But it is much, much cheaper.
they now have a classifier that lets you input random text and tells you the language it was probably written in.
Incidentally, Google Translate does this and starts guessing the source language as you start typing. I found it interesting that when you type a single character, w is guessed as Polish, i is Norwegian, s is Czech, e is Portuguese...
Whenever I see the term "prediction" applied to software, I immediately think of the books "The Eudaemonic Pie" and "The Predictors." I guess they've spoiled me.
The purpose of the example was to show how the Prediction API can recognise the language used just from a few words. So, the data given to the API is a few words in French, and it's prediction is that the language is French. I believe that they're already using this technology in Google Translator. You just type in a few words and it immediately recognises what language is being used. Then you only need to choose the language to which the text is to be translated.
Comments
As a non-techie, I don't understand the language example they're using. It seems to me many prediction engines are originally built to try to forecast winning lottery numbers or other such gambling events. Google expects me to believe they did this for language?
The point is that they took a large number of documents, which are clearly labelled as to language, gave it as a training set to the machine, and they now have a classifier that lets you input random text and tells you the language it was probably written in.
In principle you can do this with any data set and any set of discrete outcomes.
In general, though, you should expect that the resulting classifier won't give you much insight on why it came up with the answers that it did. Plus it frequently is less accurate than a trained human. But it is much, much cheaper.
they now have a classifier that lets you input random text and tells you the language it was probably written in.
Incidentally, Google Translate does this and starts guessing the source language as you start typing. I found it interesting that when you type a single character, w is guessed as Polish, i is Norwegian, s is Czech, e is Portuguese...
Frequency of first-character of words in those languages.
Whenever I see the term "prediction" applied to software, I immediately think of the books "The Eudaemonic Pie" and "The Predictors." I guess they've spoiled me.
The purpose of the example was to show how the Prediction API can recognise the language used just from a few words. So, the data given to the API is a few words in French, and it's prediction is that the language is French. I believe that they're already using this technology in Google Translator. You just type in a few words and it immediately recognises what language is being used. Then you only need to choose the language to which the text is to be translated.