Categoria: AI

Artigos marcados como AI

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Elasticsearch open inference API adds support for IBM watsonx.ai Slate embedding models
Elasticsearch Labs

Elasticsearch open inference API adds support for IBM watsonx.ai Slate embedding models

How to use IBM watsonx™ Slate text embeddings when building Search AI experiences with Elasticsearch vector database.

Saikat Sarkar
Federated SharePoint searches with Azure OpenAI Service On your data
Elasticsearch Labs

Federated SharePoint searches with Azure OpenAI Service On your data

Using Azure OpenAI Service on your data with Elastic as vector database.

Gustavo Llermaly
GenAI for customer support — Part 5: Observability
Elasticsearch Labs

GenAI for customer support — Part 5: Observability

This series gives you an inside look at how we're using generative AI in customer support. Join us as we share our journey in real-time, focusing in this entry on observability for the Support Assistant.

Andy James
GraphQL meets Elasticsearch: Building scalable, AI-ready apps with Hasura DDN
Elasticsearch Labs

GraphQL meets Elasticsearch: Building scalable, AI-ready apps with Hasura DDN

GraphQL offers an efficient and flexible way to query data. This blog will explain how Hasura DDN works with Elasticsearch to make high performing and metadata-driven access to data.

Praveen Durairaju
GitHub Assistant: Interact with your GitHub repository using RAG and Elasticsearch
Elasticsearch Labs

GitHub Assistant: Interact with your GitHub repository using RAG and Elasticsearch

This blog introduces a GitHub Assistant using RAG with Elasticsearch to enable semantic code queries, providing insights into GitHub repositories, which can be extended to PRs feedback, issues handling, and production readiness reviews.

Fram Souza
From PDF tables to insights: An alternative approach for parsing PDFs in RAG
Elasticsearch Labs

From PDF tables to insights: An alternative approach for parsing PDFs in RAG

An alternative approach to parsing PDF tables for RAG, overcoming the limitations of highly normalized formats like CSV and JSON.

Sunile Manjee
Unlock the power of your data with RAG using Vertex AI and Elasticsearch
Elasticsearch Labs

Unlock the power of your data with RAG using Vertex AI and Elasticsearch

Unlock your data's potential with RAG using Vertex AI and Elasticsearch. This blog series covers data ingestion into Elasticsearch for a robust knowledge base for creating advanced RAG based search applications.

Juan Bustos
Which job is the best for you? Using LLMs and semantic_text to match resumes to jobs
Elasticsearch Labs

Which job is the best for you? Using LLMs and semantic_text to match resumes to jobs

Learn how to use Elastic's LLM Inference API to process job descriptions, and run a double hybrid search to find the most suitable job for your resume.

Han Xiang Choong
LangChain4j with Elasticsearch as the embedding store
Elasticsearch Labs

LangChain4j with Elasticsearch as the embedding store

LangChain4j (LangChain for Java) has Elasticsearch as an embedding store. Discover how to use it to build your RAG application in plain Java.

David Pilato
Comparing ELSER for retrieval relevance on the Hugging Face MTEB Leaderboard
Elasticsearch Labs

Comparing ELSER for retrieval relevance on the Hugging Face MTEB Leaderboard

This blog compares ELSER for retrieval relevance on the Hugging Face MTEB Leaderboard.

Aris Papadopoulos
Automating traditional search with LLMs & Elastic Query DSL
Elasticsearch Labs

Automating traditional search with LLMs & Elastic Query DSL

Learn how to use LLMs to write Elastic Query DSL and query structured data with filters.

Han Xiang Choong
Quickly create RAG apps with Vertex AI Gemini models and Elasticsearch playground
Elasticsearch Labs

Quickly create RAG apps with Vertex AI Gemini models and Elasticsearch playground

Quickly create a RAG app with Vertex AI Gemini models and Elasticsearch playground

Jeff Vestal

Pronto para criar buscas de última geração?

Uma pesquisa suficientemente avançada não se consegue apenas com o esforço de uma só pessoa. O Elasticsearch é impulsionado por cientistas de dados, especialistas em operações de aprendizado de máquina, engenheiros e muitos outros que são tão apaixonados por buscas quanto você. Vamos nos conectar e trabalhar juntos para construir a experiência de busca mágica que lhe trará os resultados desejados.