Silicon Valley firms are rushing to train artificial intelligence models with tens of thousands of graphics processing units, and offering multimillion-dollar salaries to star researchers. Meanwhile, in Mongolia, Badral Sanlig is building a large language model with only 128 GPUs and a small team of engineers to serve just his country.
Sanlig’s startup, Egune AI, is part of a growing movement to build LLMs in low-resource languages to expand AI access for underserved populations. Despite a shortage of training data, compute power, talent, and funding, these small models are attracting government clients and individual users keen to safeguard their language, cultural identity, and sovereignty in the face of dominance by American and Chinese firms.
A software engineer trained in Germany, Sanlig began developing Mongolian speech recognition models in 2019, after noticing that smart devices like Alexa often struggled to understand his native tongue. Weeks after OpenAI launched ChatGPT in November 2022, Sanlig started working on an LLM. He named the startup Egune, which means “it” in Mongolian, he told Rest of World.
“The early stage was very difficult, because we didn’t have a lot of GPUs or a lot of money,” the 45-year-old said. “But we believed that LLMs could solve our language [recognition] problem because OpenAI had proved it.”
