Researchers from Microsoft recently announced they’ve created the first deep learning translation system capable of translating sentences of news articles from Chinese to English with the same level of accuracy as a person.
Microsoft used NVIDIA Tesla GPUs and millions of sentences from various online newspapers to train their neural network. The team used a dual learning system where the AI would reverse the translation to see how well it did.
Once trained, the researchers used GPUs on the Microsoft Azure cloud for inference which was able to achieve human parity.
To verify the accuracy of the results, Microsoft hired independent bilingual language consultants.
“Hitting human parity in a machine translation task is a dream that all of us have had,”Xuedong Huang, a technical Microsoft fellow said in a company blog. “We just didn’t realize we’d be able to hit it so soon,” he added.
One of the reasons translation is such a challenge is because there’s rarely one right way to do it.
The team cautioned that the breakthrough does not mean that machine translation is a solved problem. However, the techniques learned in the test will be useful for improving machine translation in other languages, and that they could be used to make other AI breakthroughs, the researchers said.
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AI-Generated Summary
- Microsoft researchers achieved human parity in Chinese-to-English news translation using a deep learning system trained on millions of sentences.
- The team employed a dual learning approach where the AI reversed translations to evaluate quality, running training on NVIDIA Tesla GPUs.
- For inference, the system used GPUs on Microsoft Azure cloud and was verified by independent bilingual consultants.
- Xuedong Huang, a Microsoft technical fellow, noted the breakthrough arrived sooner than expected, though the team cautioned machine translation remains unsolved.
Next Steps
- Explore the Microsoft Translator neural demo to see a portion of the human parity model in action.
- Read the Microsoft AI blog announcement for full details on the research.
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