Large language models (LLMs) are revolutionizing public sector services by enhancing citizen engagement and data-driven decision-making. However, off-the-shelf models often lack the cultural and regulatory specificity required for domain-critical applications. Custom LLM development provides tailored solutions, addressing inaccuracies inherent in commercial models. This blog outlines the lifecycle of developing custom LLMs for public agencies, emphasizing key stages like requirements definition, model training, and performance testing, while ensuring compliance with legal frameworks.
National LLMs focus on local languages and cultural nuances, like Greece’s initiative to preserve Greek linguistic heritage. Domain-specific LLMs cater to sectors like healthcare and finance, enhancing accuracy. Organizations must analyze costs between managed APIs and self-hosting. The optimal approach typically involves mid-sized open-source models hosted locally, ensuring data sovereignty and cost efficiency. Adopting rigorous evaluation frameworks and data curation practices using tools like NVIDIA’s NeMo Curator can enhance development outcomes, leading to more effective public service delivery.
Source link
