Neural Machine Translation - The New Kid on the Block
You notice some of the techs that turn heads nowadays; those are all front-end. The back-end tech that goes behind-the-scenes does not make the headline. However, in a transformative innovation of sorts, Neural Machine Translation (NMT) has arrived onto the translation industry, disrupting the traditional monopoly of Google and Systran.
So how does it change the financial eco-system, locally and globally? NMT being a deep learning technology, not just translates one word at a time, but more importantly, within context. And the recent developments have made it possible to translate fluently, making previous versions of machine translation obsolete overnight. So the impact that NMT will have on the global economy is huge and in many different ways.
NMT is predicted to have significant impact and effect on the fortunes of small businesses. According to Small Business Administration, these businesses employ 99.7 percent of the U.S workforce and are the primary driving force of the US economy. However, due to them being financially limited, their international reach is restricted and their affordability of multi-lingual specialists to run remote offices is questioned. With NMT, a retailer in North Dakota can market her products across the five continents.
Also, NMT opens up isolated areas to the global market. While small businesses lack the resources to penetrate remote markets, it is also true that companies in remote places have not been able to access or reach the global marketplace – due to the language barrier constraining the handling of transactions and marketing of products and services.
Likewise, NMT enables – Automatic translation of documents with reliable accuracy and precision, which previously required a team of highly skilled linguists. Subsequently, changing the way some industries work. For example, the legal eDiscovery industry which demands a nuanced approach and human intuitions to access emails, chats and online communications in other languages.