Hugging Face is taking its first step into machine translation this week with the release of more than 1,000 models. Researchers trained models using unsupervised learning and the Open Parallel Corpus (OPUS). OPUS is a project undertaken by the University of Helsinki and global partners to gather and open-source a wide variety of language data sets, particularly for low resource languages. Low resource languages are those with less training data than more commonly used languages like English.
Models trained with OPUS data now make up the majority of models provided by Hugging Face and the University of Helsinki’s Language Technology and Research Group the largest contributing organization. Before this week, Hugging Face was best known for enabling easy access to state-of-the-art language models and language generation models, like Google’s BERT, which can predict the next characters, words, or sentences that will appear in text. The Hugging Face Transformers library for Python includes pretrained versions of advanced and state-of-the-art NLP models like versions of Google AI’s BERT and XLNet, Facebook AI’s RoBERTa, and OpenAI’s GPT-2.
https://huggingface.co h/t: VentureBeat
Progress announced the release of Progress Sitefinity 13 Digital Experience Platform (DXP). The new release includes:
- A new productivity environment to manage digital assets and classify content in a consistent and resource-efficient manner
- The ability to control the look and feel of the presentation layer while delivering content to a myriad of channels. This is possible through the new page layout service that decouples content from presentation when distributed to external channels.
- Personalization based on custom tags such as title, campaign source or other attributes as well as consistent, personalized experiences for returning visitors, regardless of the initial touch point.
- Customer journey and online touchpoint monitoring based on machine learning, enabling marketers to receive proactive touchpoint alerts in order to spot new opportunities and improve the ROI of marketing campaigns.
- Data-driven analytics to measure the performance of content with a comprehensive view of all personalization initiatives as well as the ability to export data directly to Google Data Studio for expanded data analysis options.
SDL announced it has advanced its partnership level with Veeva Systems (“Veeva”), supporting the product life cycle for pharmaceutical and Life Sciences companies. SDL Translation Management System (TMS) is integrated with the Veeva Vault RIM Suite, a cloud-based Regulatory Information Management (RIM) system. In the biopharmaceutical sector, companies must react quickly to complex regulatory updates across multiple regions. The combination of SDL’s network of in-house certified medical translators with SDL’s translation management technology provides an integrated set of translation capabilities within Veeva Vault RIM. This integration enables Veeva Vault RIM customers to automate multilingual tasks relating to regulatory document submissions, engagement with health authorities and product registration. SDL joined Veeva Systems’ Technology Partner Program in 2018. https://www.sdl.com