Microsoft claims it has created an AI system that “can translate sentences of news articles from Chinese to English with the same quality and accuracy as a person.”
Says the company on its blog:
“Researchers in the company’s Asia and U.S. labs said that their system achieved human parity on a commonly used test set of news stories, called newstest2017, which was developed by a group of industry and academic partners and released at a research conference called WMT17 last fall. To ensure the results were both accurate and on par with what people would have done, the team hired external bilingual human evaluators, who compared Microsoft’s results to two independently produced human reference translations.”
Notably, Microsoft wasn't even sure it could achieve this breakthrough.
“Hitting human parity in a machine translation task is a dream that all of us have had,” said Xuedong Huang, a Microsoft machine learning lead. Huang admitted the breakthrough happened faster than expected.
“We just didn’t realize we’d be able to hit it so soon."
The breakthrough will help Microsoft's products translate text better. But it has implications beyond language translation.
“Although academic and industry researchers have worked on translation for years, they’ve recently achieved substantial breakthroughs by using a method of training AI systems called deep neural networks," the company wrote.
"That has allowed them to create more fluent, natural-sounding translations that take into account an even broader context than the previous approach, known as statistical machine translation.”
The project team combined this newer AI tech with other types of AI training methods. Said Tie-Yan Liu, a member of the team:
“Much of our research is really inspired by how we humans do things.”
The methods used on this project may apply to other projects and situations, too, says the company. Ming Zhou, another team member, says:
“This is an area where machine translation research can apply to the whole field of AI research,” he said.
This is an important point for marketers. You don’t need to understand all the technical aspects of AI and machine learning. But you should understand what’s possible. Breakthroughs in one type of AI can translate into developments in unrelated competencies.
In other words, AI developments in one industry could affect marketing. And it may happen faster than you expect.
Translation? Start reading up on artificial intelligence outside the marketing industry now.
As Chief Content Officer, Mike Kaput uses content marketing, marketing strategy, and marketing technology to grow and scale traffic, leads, and revenue for Marketing AI Institute. An avid writer, Mike has published hundreds of articles on how to use AI in marketing to increase revenue and reduce costs. Mike is the co-author of Marketing Artificial Intelligence: AI, Marketing and the Future of Business (Matt Holt Books, 2022). He is also the author of Bitcoin in Plain English, a beginner’s guide to the world’s most popular cryptocurrency.