Building large language models for the public sector on AWS

This comprehensive AWS Public Sector Blog article provides a detailed guide to building large language models (LLMs) for public sector organizations, highlighting the importance of custom LLM development to address specific regulatory, cultural, and operational requirements.

• Two primary types of custom LLMs are discussed: • National LLMs reflecting specific country/regional linguistic nuances • Domain-specific LLMs optimized for specialized sectors like healthcare and legal services
• The development process involves six key stages: • Use case and requirements definition • Evaluation framework establishment • Model selection and training approach • Data collection and preparation • Infrastructure provisioning • Production deployment and performance testing
• Key considerations include: • Cost analysis and total cost of ownership • Data sovereignty and compliance requirements • Performance and adaptation metrics • Infrastructure and compute options
• AWS provides multiple tools and services to support custom LLM development, including Amazon SageMaker, EC2, and specialized AI infrastructure

The article emphasizes that successful custom LLM development requires a systematic, scientifically rigorous approach balancing innovation with security and compliance needs.