How to get LLM apps ready for production
Deploying LLM applications to production is intricate, encompassing robust data management, ethical foresight, efficient resource allocation, diligent monitoring, and alignment with behavioral guidelines. Practices to ensure deployment readiness involve:
- Data management: Rigorous attention to data quality is critical to avoid biases that can emanate from imbalanced or inappropriate training data. Substantial efforts in data curation and ongoing scrutiny of model outputs are required to mitigate emerging biases. It’s also crucial to develop standardized datasets with relevant benchmarks to test and measure model capabilities while also detecting regressions and ensuring alignment with org/business goals.
- Ethical deployment and compliance: LLM applications are capable of generating harmful content, which calls for strict review processes, safety guidelines, and compliance with regulations such as HIPAA, especially in sensitive...
