Elastic Enterprise Search: Next-gen search experiences backed by ML

Elastic Enterprise Search is advancing its next-generation search experiences by integrating machine learning (ML) capabilities to enhance search relevance and semantic search through Elasticsearch. At ElasticON Global 2021, Elastic outlined plans to provide flexible solutions that cater to varying levels of customization, from simple out-of-the-box setups to highly tailored implementations. The company is focusing on two main ML advancements: behavioral-based models that refine search relevance using user behavior data and natural language-based models that support semantic search, enabling searches with everyday language. Investments in model management, semantic search, and technologies like dense vector search aim to bring true natural language understanding to Elasticsearch. Elastic is also enhancing user experience by integrating search tools into Kibana, simplifying data ingestion with runtime fields and web crawlers, and offering personalized connections to popular enterprise tools. Moving forward, Elastic seeks to balance simplicity with comprehensive control, providing users with intuitive interfaces while unlocking deeper functionalities through advanced ML tools.

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