SYSTRAN and TAUS have agreed to collaborate on creating a solid supply of data and models for trainers and developers of machine translation engines. Continue reading
The TAUS Transcreation Best Practices and Guidelines is published with the hope of forming a useful basis for further, industry-wide discussion around the definitions and processes of transcreation. Continue reading
TAUS publishes the first DQF Business Intelligence Bulletin for the translation and localization industry. Continue reading
TAUS launches Matching Data: a new technique of selecting language data for the training and tuning of machine translation (MT) engines. This new approach is a perfect fit for the new generation... Continue reading
24-page report. Blockchain and Translation industry overview. ICOs, business use-cases, solution analysis, crypto chatter and further reading, a cautionary tale. Continue reading
Lionbridge Technologies announced that several of its company innovators will lead discussions and thought leadership sessions at the TAUS Annual Conference in San Jose, California. Continue reading
In 2015, four leading European institutions and companies set out to solve machine translation’s four main problems: training, context, scalability, and data collection. After a brief scare when... Continue reading
As language translation emerges as a yardstick for progress in artificial intelligence, high quality human translation data becomes a prized asset. The race for AI leadership sees Baidu host... Continue reading
The new DQF plugin supports both productivity tracking and quality review based on the harmonized MQM-DQF error typology. Continue reading
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