When a language you don’t understand appears in your Facebook News Feed, you can touch a button and quickly translate it. Facebook offers a way of communicating not just with the millions of people who speak your language, but with millions of others who speak something else. Or at least it almost does.
當你的臉書動態消息中出現了一種你不懂的語言，你可以點擊一個按鈕迅速翻譯這些內容。臉書提供了一種方法使你不僅可以與數百萬會講你的語言的人交流，還可以與數百萬講其他語言的人交流�；蛘咧辽倏梢哉f臉書幾乎做到了。
This morning, the company’s central artificial-intelligence lab released a paper describing a new technology that could accelerate the evolution of machine translation not only inside Facebook but across the internet. According to Facebook’s tests, its technique does so far more efficiently than other methods, which could eventually lead to even sharper translations.
今天上午臉書公司人工智能中心實驗室發表了一篇論文，介紹了一種可以加速機器翻譯發展的新技術，這種技術不僅可以加速臉書公司機器翻譯的發展，還可以加速整個互聯網機器翻譯的發展。據臉書內測顯示，迄今為止，這項技術比其他方法更有效率，最后還可以使翻譯的內容更清楚明確。
Facebook’s approach relies on neural networks, complex mathematical systems that can learn tasks by analyzing vast amounts of data. This past fall, Google unveiled a new translation system driven entirely by neural networks that topped existing models, and many other companies and researchers are pushing in the same direction, most notably Microsoft and Chinese web giant Baidu.
臉書的方法依賴于神經網絡和復雜的數學系統，可以通過分析大量的數據來獲悉任務。去年秋天谷歌推出了一款完全由神經網絡驅動的新型翻譯系統，該系統超過了所有的現有模型，而且許多其他公司及研究人員也在朝著相同的研究方向推進，特別是微軟和中國網絡巨頭百度。
But Facebook is taking a slightly different tack from most of the other big players. It’s using what are called convolutional neural networks, a technique invented by the venerable researcher Yann LeCun, who now oversees Facebook’s AI lab. Rather than analyze a sentence sequentially, one piece at a time, a convolutional neural network can analyze many different pieces at once, before organizing those pieces into a logical hierarchy.
不過臉書采用了一種與其他多數行業巨頭略有不同的方法，它使用了一種所謂的卷積神經網絡，該技術是由德高望重的研究員揚·勒丘恩發明的，如今勒丘恩管理著臉書的人工智能實驗室。卷積神經網絡可以同時分析許多不同的內容，然后把這些內容組織成合乎邏輯結構的句子，而不是按順序一次一段地分析一個句子。
Even if the system is only marginally more accurate than systems like the one Google rolledout in the fall, the company says its technique is more efficient that other neural network-based methods.
雖然這個系統只比谷歌秋季推出的系統略微準確一些，但臉書公司表示，這項技術要比以神經網絡為基礎的其他方法更有效率。
Others may help push the technique forward as well. Facebook is not only publishing a paperdescribing its new system but open-sourcing the software engine that drives the system, freelysharing the code with the world at large. It means that translation will evolve far more quicklyacross the internet—not just on Facebook.
其他人或公司也可以幫助推進這項技術的發展，因為臉書公司不僅發表了介紹其新系統的論文，還公開了驅動系統軟件引擎的源代碼，免費與全世界分享這個系統的代碼。這意味著，不僅僅是臉書公司，整個互聯網的翻譯技術都會更迅速地發展下去。
