When you create a recipe, you try a few tweaks and combinations before landing on the final v...
When you create a recipe, you try a few tweaks and combinations before landing on the final version. Creating an embedding model is no different. This process of experimentation is known as ablation. For both audio and vision pipelines in jina-embeddings-v5-om
Before EIS: CPU nodes, self-managed, one per model.
Before EIS: CPU nodes, self-managed, one per model. After EIS: 1 GPU-accelerated fleet, managed by Elastic. Vector search and semantic reranking each ran on CPU nodes you provisioned yourself. More models meant more infrastructure to operate. The Elastic Infer