AI translation

Organizations often ask how much multilingual content AI can handle. The more important question is whether every piece of content should be handled in the same way.

Artificial intelligence has dramatically reduced the effort required to create multilingual content. Organizations can now translate, adapt and generate content at a speed that would have been difficult to imagine only a few years ago. But greater production capacity does not automatically lead to better multilingual communication because it has also introduced an entirely new management challenge that most organizations have yet to recognize.

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 While many organizations still rely on intuition or outdated market assumptions, forward-thinking companies are embracing a fundamentally different approach—one powered by data, precision, and strategic insight.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 today’s digital age, the landscape of language services has undergone a dramatic transformation. With the advent of free translation tools, many wonder about the future of language service providers (LSPs). At Ciklopea, we’re not only adapting to these changes, but have evolved to offer unparalleled value in this new ecosystem.

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 As companies scale globally, the size of their TMs grows exponentially, which can lead to inconsistencies, outdated translations, and even redundant content.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?

It’s a story that’s as old as time. Every time a new technology emerges, you have two groups of people. One group is excited about the potential applications and the other panics about the change ahead and potential disruption. AI in the translation industry has sparked similar reactions.

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.