Part 6/11:
Scalability: As data grows, maintaining high performance and swift retrieval becomes more complex.
Search relevance: Fine-tuning search indexes and embeddings to ensure meaningful results.
Data privacy and security: Metadata and conversation logs contain sensitive information requiring proper protection (GDPR, CCPA compliance).
Cost management: Large language models (LLMs) are expensive—emphasizing the need to offload as much work as possible to faster, cheaper search and retrieval systems.
He stresses the need to balance reliance on large, costly models with efficient retrieval systems, like semantic search, support vector machines, or classification models that can predict relevance, rather than querying for full inference every time.