Back in May, the company’s artificial intelligence division, called Facebook AI Research, announced that they had developed a kind of neural network called a CNN (that stands for convolutional neural network, not the news organization where Wolf Blitzer works) that was a fast, accurate translator. Part of the virtue of that CNN is that instead of looking at words one at a time, it can consider groups of them.
Now, Facebook says that they have incorporated that CNN tech into their translation system, as well as another type of neural network, called an RNN (the R is for recurrent). Those RNNs, Facebook said in a blog item about the news, are better at understanding the context of the whole sentence than the previous system, and can reorder sentences as needed so that they make sense.
As an example of the difference between the two translation systems, Facebook demonstrated how the old approach would have translated a sentence from Turkish into English, and then showed how the new AI-powered system would do it. The first Turkish-to-English sentence reads this way: “Their, Izmir’s why you said no we don’t expect them to understand.” Now check out the newer translation: “We don’t expect them to understand why Izmir said no.” Notice how the AI fixed the mistakes in word and phrase order?
While neural networks had been working together with the more traditional translation system before today, now all the translation gets its smarts from AI.
The new system is more accurate than the old method...
What a nice Post!! Thanks Nikita for sharing it!!
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