Translated CEO Marco Trombetti on Time-to-Edit as Proxy for AI Singularity
Translated CEO, Marco Trombetti, on their Singularity in AI research, working with enterprise clients like Airbnb, and the symbiosis between human and machine.
ModernMT
Translated Secures USD 25m in Growth Equity at Nine-Figure Valuation
Translated secures USD 25m from PE firm Ardian, earning the Italy-based language service provider a nine-figure valuation as it plans to boost research into human-in-the-loop translation.
Isabelle Andrieu on Building Translated and Venture Investing Through Pi Campus
Translated Co-founder and Chairman Isabelle Andrieu talks about building a tech-driven LSP and supporting and funding startups via the Pi Campus and Pi School she leads.
Language Industry Hires at Språkservice, Translated, IDC, and Comunica
Språkservice adds a Head of Sales & Business Development; Translated, a VP Americas; IDC, a Director of Localization; and Comunica, a Sales & Vendor Manager.
Use of ModernMT in IP and Life Science Translations: an ASTW Case Study
Interview with Davide Caroselli, Product VP of ModernMT, the context-aware machine translation that learns from user corrections.
Machine Dubbing: Amazon AI Opens New Chapter in Automating Media Localization
Team of Amazon AI researchers combines various deep-learning models to build automatic dubbing system. Viewer feedback reveals unnaturalness of speaking rate as main problem.
Slator 2019 Language Industry Market Report
Slator’s inaugural comprehensive language industry market report. It examines total market size, the 10 main end-buyer industries, competitive landscape, productivity tech, NMT and much more.
MMT Brings Adaptive Neural MT to MateCat and to MyMemory Plugin for SDL Trados
Efficiency boost for tens of thousands of translators as MMT launches the first ever adaptive neural machine translation plugin for two of the most widely used translation productivity tools, SDL Trados Studio and MateCat.
Business and Academia Join Forces to Launch Next-Gen Machine Translation
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 Google Translate went neural, the project is now in beta and set for enterprise-grade release in Q4 2017.
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