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Stefan Huyghe is a seasoned language industry professional with over 20 years of experience. He currently is Vice President of Localization at Communicaid Language Solutions. Passionate about sharing knowledge, Stefan is a respected Translation Industry Writer, Content Creator, and host of LocDiscussion, a monthly online localization roundtable networking event that tackles the latest trends in the industry. He has developed a loyal following on LinkedIn and is a social selling expert. Through his articles and social media posts, he delivers engaging and informative thought leadership on topics like language, localization, multilingualism, artificial intelligence, social selling, and guerrilla marketing. Stefan’s contributions are regularly featured in MultiLingual Magazine and on Nimdzi Live. He is also the author of the AI-in-Loc newsletter which has over 4000 subscribers and tracks Artificial Intelligence developments in localization at the intersection of language and technology. Stefan is a recognized and influential Globalization Consultant who has helped numerous companies navigate the complexities of expanding their businesses internationally. His deep understanding of cultural nuances and the intricacies of language allows him to provide valuable insights and strategies for seamless global communication. Born in Belgium and raised in Switzerland, Stefan embodies the essence of multilingualism. Fluent in 4 languages, he has a profound appreciation for the power of language and its impact on cross-cultural communication. Residing in the United States since 1993 has given him a deep understanding of both the American and European business markets.
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“More data” isn’t the answer. Structured, relevant, multilingual content is. That was one of the big takeaways from my recent interview with (Samuel) Yongrui Su, CEO and CTO of Chat Data, a platform that enables businesses, regardless of technical background, to deploy intelligent, domain-specific AI chatbots trained on their own content. Yongrui isn’t from the localization world but he’s building AI infrastructure that makes our expertise indispensable. His platform lets non-technical users create domain-specific chatbots trained on their own content and what those bots need most to function well is what we, as localization professionals, already have: Clean, aligned data like translation memories, curated multilingual datasets, terminology bases, context-rich domain knowledge. In our conversation, Yongrui breaks down why generic data often leads to generic (or wrong) results, how retrieval-augmented generation works under the hood, and why high-quality localization assets are rapidly becoming premium AI training fuel. We also explore how prompting shapes chatbot personality, how multilingual UX design is evolving, and why “language-aware” infrastructure is now essential not optional. The future is best trained on human-validated content and that’s where the localization industry could come in. What do you think?
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