Ready to build a RAG app with Go? Follow along to learn how to create the RAG application using Ollama to leverage local models: https://t.co/FoLyG8GbMN
#ElasticSearchLabs
Check out this blog to discover how we optimized vector comparisons in BBQ with hardware-accelerated Single Instruction Multiple Data (SIMD) instructions: https://t.co/dz2mCLLCKI
#ElasticSearchLabs
Easily crawl websites and make them semantically searchable. This blog explains how to use the Open Crawler with semantic text. Check it out: https://t.co/mVOOctamL6
#ElasticSearchLabs
Enhance LLM observability with Elastic's @googlecloud Vertex AI Integration and gain actionable insights into model performance, resource efficiency, and operational reliability. Learn more here: https://t.co/RiJWgLYITk
#ElasticObservabilityLabs
Level up your Vega visualizations in Kibana. Learn how to create Kibana filters with Vega using the kibanaAddFilter function. Dive in now: https://t.co/76EaJPed1C
#ElasticSearchLabs
Ramp up in Search AI today. Try out these four self-paced hands-on learning lessons that will help you get started in lexical search, semantic search, vector search, and how to build your own RAG app.
Learn more → https://t.co/GYyyMTTXxg
Guest post alert! GraphQL is an efficient and flexible way to query data. @praveenweb from @HasuraHQ explains how Hasura DDN works with Elasticsearch to enable high-performance, metadata-driven access to data. Learn more: https://t.co/JO7rLSByoB
#ElasticsearchLabs
If you ever wondered how @huggingface models could be used to perform semantic-reranking in Elasticsearch, wonder no more. Check out this blog to learn more: https://t.co/12QoGcqhFT
#ElasticSearchLabs
Episode 5 of 'You Know, For Search' is live! Featured guest @benwtrent discusses the importance of quantization: https://t.co/NUyPKYFhLm
Let host @smayzak know — what's been your favorite episode to date? What topics do you want to hear next?
Ready to build a RAG app? Get started by learning how to create a RAG application using Elastic’s generative AI capabilities with this hands-on guide.
Check it out → https://t.co/LHUMUbJJhX
A fun and furry search app for cats! 🐱
With different types of search: lexical, vector, and hybrid — on multiple embeddings. Dive into this blog to learn how to write a simple and playful search application on cats: https://t.co/HlufIgxRvZ
#ElasticSearchLabs
Learn how to integrate your custom model to create vector embeddings, configuring Elasticsearch for vector search, and running queries to retrieve contextually relevant results. Dive into this Search AI 101 guide for vector search to learn more → https://t.co/KlrkoFWRpW
Now live! Elastic 8.17 includes Elasticsearch’s specialized logsdb index mode, now GA, which reduces storage footprint of log data in Elasticsearch up to 65%, Elastic Rerank model, full text search for ES|QL, hybrid search improvements & more.
Dive in → https://t.co/6CNT7fPsmu
cRank it up — Introducing Elastic Rerank Model to power up semantic search!
Amplify your search experiences through semantic boosting with no required reindexing. Learn more: https://t.co/Mj24u24zeg
Discover how to troubleshoot Index Lifecycle Management (ILM) issues with the ILM History index. From filtering data for insights to setting up alerts, learn how to ensure smooth index transitions in our latest blog: https://t.co/EyIs5OIzad