How does machine learning work according to this article?

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The discussion centers on the concept of machine learning as described in an article from The Atlantic, which outlines a method for translating English sentences into French using a simplified machine model. The machine operates by randomly generating French words for given English words, with various adjustable parameters or "knobs" that influence its output. The process involves feeding known English-French sentence pairs into the machine, adjusting the parameters based on the accuracy of the translations produced, and iteratively refining the machine's ability to generate correct translations. There is some confusion regarding the terminology used, particularly the meaning of "feed" in the context of entering sentences into the machine, as well as the nature of the pairs being referenced. The methodology is likened to a weighted neural network, suggesting a structured approach to improving translation accuracy through machine learning techniques. Additional resources on natural language processing are recommended for further understanding.
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From an article published on the Atlantic ( http://www.theatlantic.com/magazine...man-who-would-teach-machines-to-think/309529/ ) :

"The technique is called “machine learning.†The goal is to make a device that takes an English sentence as input and spits out a French sentence. One such device, of course, is the human brain—but the whole point is to avoid grappling with the brain’s complexity. So what you do instead is start with a machine so simple, it almost doesn’t work: a machine, say, that randomly spits out French words for the English words it’s given.

Imagine a box with thousands of knobs on it. Some of these knobs control general settings: given one English word, how many French words, on average, should come out? And some control specific settings: given jump, what is the probability that shot comes next? The question is, just by tuning these knobs, can you get your machine to convert sensible English into sensible French?

It turns out that you can. What you do is feed the machine English sentences whose French translations you already know. (Candide, for example, used 2.2 million pairs of sentences, mostly from the bilingual proceedings of Canadian parliamentary debates.) You proceed one pair at a time. After you’ve entered a pair, take the English half and feed it into your machine to see what comes out in French. If that sentence is different from what you were expecting—different from the known correct translation—your machine isn’t quite right. So jiggle the knobs and try again. After enough feeding and trying and jiggling, feeding and trying and jiggling again, you’ll get a feel for the knobs, and you’ll be able to produce the correct French equivalent of your English sentence."


......


I did not understand what the writer said in the second paragraph ( Imagine a box ... sensible French. ) I also did not understand what he meant by "After you’ve entered a pair, take the English half and feed it into your machine". Does "feed" here mean "enter"? If it does, how can one enter a sentence that has already been entered?
 
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jedishrfu said:
I think the pair was a pair of words and the methodology he was describing was probably a weighted neural network.

You can read more about this on Wikipedia:

http://en.wikipedia.org/wiki/Natural_language_processing

Thank you very much.
 
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