The boards of RWS and SDL announced they “have reached agreement on the terms of a recommended all-share merger of RWS and SDL,” in a deal that sees RWS buy SDL outright. The transaction values SDL shares at a 52% premium over SDL’s most recent share price. SDL shareholders will own approximately 29.5% of the combined group, with RWS shareholders owning 70.5%. The SDL brand will disappear, and all SDL units rebranded as RWS over time. The combined company will remain listed on London’s AIM market and keep its HQ in Chalfont St Peter (UK). The deal is expected to be completed in Q4 2020, and RWS said they expect the transaction to result in double-digit earnings per share accretion. With pro forma FY2019 revenues of GBP 732m (USD 967m) and adjusted operating profit of GBP 116m, the combined organization will become the largest language service provider by revenue.
RWS emphasized the two businesses’ highly complementary nature as well as combining its services business with SDL’s proprietary technology and translation workflow software as key drivers of the deal. RWS said that after consulting with SDL management they expect at least GBP 15m in annualized cost savings from the deal. Andrew Brode, Chairman of RWS, will become Chairman of the Board of the Combined Group. Richard Thompson, CEO of RWS, will become CEO of the Combined Group. Desmond Glass, CFO of RWS, will become CFO of the Combined Group. From SDL, Azad Ootam, CTO of SDL, will become CTO of the Combined Group. Current SDL CEO Adolfo Hernandez and SDL CFO Xenia Walters will leave the company, but RWS said they “will enter into a new service or consultancy agreement with RWS.”
Yext, Inc. announced “Milky Way,” the latest upgrade to the natural language processing (NLP) algorithm that powers Yext Answers, Yext’s site search product. Headlining this milestone update is the adoption of BERT, (Bidirectional Encoder Representations from Transformers). Developed by Google, BERT is an open source machine learning framework for NLP designed to better understand user searches. By leveraging BERT within Named Entity Recognition (a process to locate and classify named entities mentioned in unstructured text into predefined categories), Yext Answers improves its ability to distinguish locations from other types of entities, including people, jobs, and events. The update includes:
- Improved Named Entity Recognition: By leveraging BERT, Yext Answers can now better understand the contextual relationship between search terms. Answers will return a more relevant result by taking into account the correct classification, whether a location, person or product.
- Improved Location Detection: The update leaves behind location biasing. Now, Yext Answers will filter through locations stored by a business in their Yext knowledge graph to surface the best match.
- Updated Healthcare Taxonomy: More than 3,000 new healthcare-related synonyms, conditions, treatments, and procedures have been added to the algorithm’s taxonomy.
- Improved Stemming and Typo Tolerance.
Connatix announced the launch of a proprietary Video Insights Engine. This new capability will leverage advanced machine learning to automatically analyze the visuals and audio within a publisher’s video content to help bring greater efficiency to editorial workflows with automatic video indexing, derive new insights from content performance, and help scale contextual offerings. The Video Insights Engine is available in Elements, their online video platform (OVP) for publishers. The Video Insights Engine is a result of last year’s acquisition and integration of Kamidoo, a company that specializes in natural language processing, and is the first installment of the technology within the Elements platform. Connatix uses its proprietary technology with natural language processing (NLP) and machine learning to identify:
- Content categories: Automatically assigns categories and sub-categories to video content.
- Detects brands and companies: Recognizes brands and companies mentioned and/or detected in videos.
- Flags mentions of famous individuals.
- Determines sentiment of video content: Provides a breakout of the positive, negative, and neutral emotions detected in videos.
This automatic video indexing and categorization technology comes as a complementary offering to Connatix’s contextual page analysis capabilities.