Event recap: SF Globalization meetup with our CEO, Spence Green

by Adrienne Lumb
1 Minute Read

We had the pleasure of joining the SF Globalization meetup this past Wednesday, Feb. 13, at the Autodesk Gallery in San Francisco, where our CEO Spence Green gave a presentation on recent advancements in neural machine translation.

Green reviewed the history of Machine Translation (MT), going back to the 1950s and over the decades since. He discussed more recent advancements, including Google Translate, but in particular our research and milestones in neural MT (NMT) in the past few years. Green also shed insights into the science behind NMT, and gave a captivating product demo.

The talk shifted to what internationalization and localization teams can do with NMT technology, and how translators can use it to make their work faster, and easier.

Green also shared questions he commonly hears from global enterprises interested in Lilt technology, and alternative questions they should be asking in seeking new and better technology and workflows.

You can view the full session here:

SF Globalization is a meetup group of more than 1,600 members, open to anyone interested in the globalization of any type or format of content. You can learn more about the group and their events here.

Localization is profitable. You can measure it.

Having a hard time tying localization to ROI? We've got you. The Ultimate Guide to Measuring Localization ROI covers everything you need to know to tie your market expansion efforts to business goals and revenue.

Get the guide
null

Interactive and Adaptive Computer Aided Translation

5 Minute Read

Originally published on Kirti Vashee’s blog eMpTy Pages. Lilt is an interactive and adaptive computer-aided translation tool that integrates machine translation, translation memories, and termbases into one interface that learns from translators. Using Lilt is an entirely different experience from post-editing machine translations — an experience that our users love, and one that yields substantial productivity gains without compromising quality. The first step toward using this new kind of tool is to understand how interactive and adaptive machine assistance is different from conventional MT, and how these technologies relate to exciting new developments in neural MT and deep learning. Interactive MT doesn’t just translate each segment once and leave the translator to clean up the mess. Instead, each word that the translator types into the Lilt environment is integrated into a new automatic translation suggestion in real time. While text messaging apps autocomplete words, interactive MT autocompletes whole sentences. Interactive MT actually improves translation quality. In conventional MT post-editing, the computer knows what segment will be translated, but doesn’t know anything about the phrasing decisions that a translator will make. Interactive translations are more accurate because they can observe what the translator has typed so far and update their suggestions based on all available information.

Read More
federica-galli-449563-unsplash

Top MT computer science concepts demystified

3 Minute Read

Computer science terms once exclusively used in scientific communities have become ubiquitously integrated into our daily lives—the news we read, products we consume, and the technology we use. Some are used interchangeably with one another (incorrectly), others are hazy in definition and application. In light of this, we thought we’d lend clarity to the top Machine Translation (MT) related computer science terms you may encounter.

Read More