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Joined October 2009

Elastic
@elastic
Aug 14
Your agent burns tokens just figuring out where to look. It inspects mappings, samples docs, probes indices. That's 12 tool calls and 167K tokens to get an answer. Knowledge Indicators fix this. A Kibana Workflow profiles each index once: purpose, key fields, routing
Elastic
@elastic
Aug 13
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-omni, multiple
Elastic
@elastic
Aug 13
Relevance Please: Ep 5 - Build Agents That Ask Before They Act x.com/i/broadcasts/1…
Elastic
@elastic
Aug 12
We batched shard queries per data node. Each data node handles partial reductions locally. Lower latency, better work distribution across the cluster.
Article
How Elasticsearch's batched query phase improves search performance at scale
The batched query phase, which is live in Elasticsearch Serverless and released in Elasticsearch 9.5.0, changes how search is coordinated across the cluster. The coordinating node now batches all...
Elastic
@elastic
Aug 11
How can a text embedding model map audio and image vectors? After being transformed via a projector (translator), a foreign modality vector must announce itself before entering an embedding model for an unrelated modality. Think of HTML. <p> These tags let the document know