Every project we undertake is a chance to prove what our technology can do for you. Some of the most significant breakthroughs don’t happen with massive, generic datasets. They happen when we solve a problem so specific, so unique, that it proves our capability to handle anything.
This is why, in our internal lab, we took on a seemingly obscure challenge: teaching a foundation model to “speak” Latvian.
Latvian is a small, complex language spoken by fewer than two million people. It has unique grammatical structures, intricate declensions, and a rich, nuanced vocabulary. For a foundation model trained on broad, global data, mastering Latvian isn’t just an incremental step—it’s a leap. It requires deep, precise fine-tuning.
This project wasn’t about the Latvian language itself. It was about proving our expertise with the most demanding AI workloads.
To accomplish this, we built a private AI environment on a Red Hat OpenShift server cluster, powered by four NVIDIA L40s GPUs. This setup gave us a secure, local platform to fine-tune the IBM WatsonX.ai foundation model. By keeping everything in-house, we validated our design-build-operate (DBO) service model and demonstrated how a modest yet powerful infrastructure can support cutting-edge AI research.
What we learned was more than just how to handle a complex language. We proved that:
This experiment was a stepping stone, not a destination. It was our way of demonstrating that we are uniquely equipped to tackle your most specific, complex, and confidential AI challenges.
Your business may not need an AI that speaks Latvian. But you might need a model that understands:
Our expertise is in taking the immense power of foundation models and refining them for your world—securely, reliably, and on your terms.
Latvian was just the beginning. Imagine what’s possible when we apply this same level of expertise and infrastructure to your unique use case. The potential is limitless.
Datakom offers a range of IT services, suitable for any institution or company, based on business needs, industry specifics and the number of employees.
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