This category explores the technological frontier of language. We dive deep into how to integrate the latest LLMs (GPT, Claude) into your workflow, and the critical need for AI quality assurance and governance. Content is designed for Localization Managers and Engineers who need to leverage AI for scale while maintaining high quality, consistency, and data security. Learn to manage translation memory (TM) alongside AI output to maximize speed and cost savings.
Machine translation (MT) is currently being employed in areas like customer support, e-commerce, healthcare, education, government resources, instruction manuals and social media in order to enable multilingual communication in a cost-effective way. While it’s been around for decades, it’s only in recent years that individuals and organizations have started relying on it for their everyday needs. So much so that, according to
Before neural networks took over, machines learned to translate by looking at patterns in large sets of human-translated texts. This approach is called Statistical Machine Translation (SMT). It was a…
Some types of machine translation systems follow strict grammar rules. Others rely on stats. Today’s most advanced ones use deep learning to mimic how humans speak. Each type has strengths,…
Neural machine translation (NMT) sounds technical and complex. But at its core, it’s just how modern AI translates one language into another. If you’ve ever used Google Translate, watched subtitles…
Natural language processing. Large language models. Two terms you’ve probably seen tossed around in AI conversations. Sometimes they’re even used like they mean the same thing. But they don’t. For example, using an LLM for translation showcases capabilities that go beyond traditional NLP approaches. Long story short, NLP is the broader field
How accurate are LLMs when translating text? It’s a fair question, one that’s becoming increasingly important as AI translation tools keep getting better and companies look for new ways to optimize costs. But you’re probably here because you’re wondering if LLMs are accurate enough to use without a human in the loop.In this article, you’ll learn how LLMs translate text, how their approach differs from traditional machine translation, and
Translation doesn’t have to be slow, expensive, or manual anymore. Thanks to AI, you can translate content into multiple languages incredibly fast. But if AI translation is so great, why do we still have human translators? What’s it all about? If you’re wondering what AI translation actually is, you came to the right place. Keep reading to discover answers to ten key questions, and learn what AI translation is all about.
Want to turn a piece of software written in Java into Python without rewriting it from scratch? This is now possible thanks to LLM for translation. What a time to be alive. Large language models (LLMs) like GPT or CodeT5 can now understand and translate programming languages. This helps developers migrate projects, modernize old codebases, and adopt ne
Behind the scenes of localization with one of Europe’s leading digital health providers
Read more Case studies
Localization workflow for your web and mobile apps, games and digital content.
©2017-2026
All Rights Reserved.
