The article explores challenges faced by low resource languages in accessing large language models (LLMs) and presents innovative strategies, like creating high-quality fine-tuning datasets, to improve LLM performance, particularly focusing on Swahili as a case study. These advancements contribute to a more inclusive AI ecosystem, supporting linguistic diversity and accessibility.
This story contains new, firsthand information uncovered by the writer.