How DeepL outmaneuvered big tech, won a following, and is now rapidly moving into machine translation as a managed service for enterprise customers. Continue reading
At SlatorCon Remote December 2020, Intento Co-founder and CEO Konstantin Savenkov discusses alternative pricing models that account for machine translation quality. Continue reading
The most-cited neural machine translation research papers show how NMT came to dominate the field — and how academia and industry’s interests have evolved. Continue reading
Machine translation company Intento uses metadata and MT-agnostic natural language processing to dodge AI biases around gender and tone of voice. Continue reading
MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL) derives algorithm to handle lack of training data, making it easier to adopt current machine translation methods. Continue reading
Logrus Global has significantly updated Prospector the terminology extraction tool confirmed as best-in-class by an independent study Continue reading
Memose is a cloud-based translation memory server with CAT-tool functionality Continue reading
Since its 2017 debut, Sockeye has powered Amazon Translate and gathered decent traction elsewhere. The new version adopts Gluon base code and gets a boost from Intel and NVIDIA. Continue reading
French machine translation provider SYSTRAN has a new owner, STIC Investments. Minority shareholders include SoftBank Korea, others. Plans M&A. Continue reading
New research suggests biases of QE datasets lead to guesstimates on machine translation quality. Researchers propose modified dataset, debut it at WMT 2020. Continue reading
Salesforce research on speeding up the work of post-editors by training MT engines with XML tags culminates in a 17-language online help dataset published on Github. Continue reading
Tech-enabled LSP Lilt raised USD 25m just in time before Covid-19 disruption. CEO Spence Green talks about how they plan to expand within the enterprise and which MT trends excite him most. Continue reading
A research paper published in April 2020 explores how to reduce gender bias in neural machine translation (NMT) using transfer learning and fine-tuning. Continue reading
Group of leading researchers finds that the way machine translation quality is evaluated by humans is broken. Group issues five recommendations on how to fix it. Continue reading
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