AI in Localization

Lightning fast, continuous localization. Decent quality. Super affordable. All automated with no humans in the loop. This guide shows you how to build a multilingual product on autopilot using Crowdin. The workflow is tech stack agnostic and suitable for web, mobile and desktop applications, as well as their documentation and marketing materials. Best of all, AI translations would be contextual. The AI will have all the information it needs to produce the best possible translations. And in the future, you would still be able to bring in a human linguists to improve translations, if you needed to. Prerequisites: You have an internationalized web or mobile application. This means that all translatable texts from the UI have been extracted into the resource files. The implementation time of this guide is 30 minutes.

Accurate translation is essential to facilitate global collaboration. Traditional translation methods often require significant time and resources. Combining Crowdin AI and human translations offers faster and more consistent results. By harnessing the power of AI, you can enhance its translation capabilities and optimize resource allocation. Discover how AI revolutionizes the localization process and workflow by enhancing translation accuracy through contextual understanding in this article.

If you're curious about how Crowdin AI can enhance your localization projects, this article answers some frequently asked questions about price, customization, and best practices. Let’s discover if an AI can translate and the best way to use AI tools for language translation. <YouTubeEmbed id="ZqfvNIMpp4Q" />

It's fascinating to watch how LLMs are taking over the translation industry. In the last few months, we've seen many great applications of how machines can assist and perform translation tasks. The reason LLM's seem to be taking over is because of the context they can accept and leverage when translating. Today, we're very excited to announce immediate access to the latest version of Crowdin AI with the fine-tuning feature! A way to feed TM's and glossaries of any size before asking the LLM to translate your content.

The first experiments with machine translation began in the 1950s. At that time, the technology was more like an automated dictionary. Machine translation became more useful in the 90s when statistical machine translation was introduced. However, the translation quality was still far from human translation. In 2010, when Google introduced Neural Machine Translation, things changed. Machine translation became a useful tool, which in many cases, influenced both the work of professional translators and clients' budgets. Now, AI is actively searching for its place within all industries, and localization is no exception. Let's see how you can run AI pre-translation and the potential of AI in localization.

Today we are happy to announce the invitation to the beta version of our new app – an AI chatbot built on OpenAI's ChatGPT API. Large language models are the hottest topic around our newsfeeds these days. While companies are still figuring out how to use them most efficiently, it is clear that this technology will change the way people and companies work in the near future. Crowdin has been experimenting with AI and ML for years to offer the most advanced technologies and make sure we enable our users to be most productive while doing global business. AI chatbot built on OpenAI's ChatGPT API we're showing today is just one of the first successful experiments we're excited to share. This is an private beta, and you're welcome to join.