Machine Translation

In today’s interconnected economy, the difference between companies that thrive globally and those that struggle often comes down to one critical factor: how they approach language strategy and localization planning. While many organizations still rely on intuition or outdated market assumptions, forward-thinking companies are embracing a fundamentally different approach—one powered by data, precision, and strategic insight. 

As large language models (LLMs) like GPT redefine how we translate and communicate across borders, one persistent issue remains: AI still struggles with South Slavic languages — especially Croatian, Serbian, Bosnian, and Slovenian. 

In the fast-paced world of localization, maintaining the accuracy and quality of Translation Memories (TMs) is essential for ensuring seamless, consistent translations. As companies scale globally, the size of their TMs grows exponentially, which can lead to inconsistencies, outdated translations, and even redundant content. That’s where AI-powered TM Cleanup comes into play. This innovative solution combines the strengths of AI with prompt engineering, revolutionizing how organizations manage their TMs.

In the evolving landscape of artificial intelligence (AI) and machine learning (ML), the role of linguistic annotation has become more important than ever. As companies and developers work to build smarter systems, from chatbots to translation tools, the need for high-quality language data is paramount. But what exactly is linguistic annotation, and why is it so important?

In our previous blog post, we tackled the common pitfalls of translation and localization projects and programs. Now, let’s dive into how a streamlined 3-step process can turn these challenges into opportunities and drive your international expansion.

Nowadays, artificial intelligence is the talk of the town. People across all industries are exploring how they can leverage AI tech to work more efficiently and optimize costs. We’re gradually pushing the limits of what’s possible, and the language solutions space is no different.

We’re excited to present our latest instalment of Ciklopea Coffee Chat, featuring a captivating conversation with Manuel Herranz, CEO of Pangeanic.

Wherever you look nowadays, AI is the talk of the town. Just think about ChatGPT, DALL-E, or similar AI systems, and you’ll see why people are so divided when it comes to the direction in which the advancement of this technology will take us.

One of the most frequent questions we get from our customers relates to the tech stack that we use. This doesn’t come as a surprise to us because translation technology can significantly reduce your project costs and it directly impacts the quality of our collaboration.

The localization landscape is extremely fragmented, and you probably noticed that it may be a bit confusing to define what types of services you really need, as well as how to deal with the non- familiar industry terminology.

Machine translation. Artificial intelligence. Neural language processing. Predictive modelling. These fancy terms have been flashing everywhere over the past several years to the point when it seems that all your localization problems can be solved with a double click. As of 2021, they can’t. In this article, we will try and explain the exact role of technology in the translation/localization process in the simplest possible terms and help you understand what it really can and cannot do for you.

We have recently had an interesting chat with Nikola Ljubešić, researcher at the Jožef Stefan Institute, Ljubljana, on the machine translation research focused on similar languages, in this case Slovenian, Croatian and Serbian.

Hot on the heels of our article on machine translation, it’s now time to discuss computer-assisted translation or CAT.

Once when I was a kid, I was passing by a car wash which had the big written sign “Machine washing and polishing” with a friend who asked me, all amazed, “Wow, they have machines to wash the cars?!” And the guy who worked there heard him and replied, mildly disappointed “Do I look like a machine to you?” We did not expect that, but he, indeed, was still a human being. Same goes with machine translation (MT).

We are pleased to announce that Ciklopea has joined the SDL LSP Partner Program. The strategic partnership helps us update and verify our SDL expertise by SDL, streamline our processes and expand the possibilities of advanced linguistic solutions. SDL Trados Studio, GroupShare and MultiTerm have been among our standard tools since the very beginning of […]

The Atomic Era conviction that computers will eliminate the need for translators – or even the need to learn foreign languages at all – within a few short years still persists. But will it?

This type of translation services uses proxy servers to render multilingual versions of a website