{"slug": "my-lab-found-a-way-to-migrate-between-embedding-models-with-zero-downtime-r", "title": "My lab found a way to migrate between embedding models with zero downtime. [R]", "summary": "A developer claims to have found a method to migrate between embedding models with zero downtime, addressing the challenge of upgrading models when dealing with large document collections. The approach is presented as a practical solution for retrieval-augmented generation (RAG) systems, particularly in local LLM contexts, to maintain grounded answers while avoiding service interruptions.", "body_md": "So I've been messinga round with embedding models for a bit, and I think they are interesting enough to experiment with. They are useful for rag, especially in a localllm sense because you can ground your answers in truth. But what happens if you have a billion documents, and you decide to upgrade y", "url": "https://wpnews.pro/news/my-lab-found-a-way-to-migrate-between-embedding-models-with-zero-downtime-r", "canonical_source": "https://aiflash.com/news/115372/", "published_at": "2026-09-08 05:00:04+00:00", "updated_at": "2026-09-08 05:31:29.940859+00:00", "lang": "en", "topics": ["machine-learning", "ai-research", "ai-infrastructure"], "entities": [], "alternates": {"html": "https://wpnews.pro/news/my-lab-found-a-way-to-migrate-between-embedding-models-with-zero-downtime-r", "markdown": "https://wpnews.pro/news/my-lab-found-a-way-to-migrate-between-embedding-models-with-zero-downtime-r.md", "text": "https://wpnews.pro/news/my-lab-found-a-way-to-migrate-between-embedding-models-with-zero-downtime-r.txt", "jsonld": "https://wpnews.pro/news/my-lab-found-a-way-to-migrate-between-embedding-models-with-zero-downtime-r.jsonld"}}