Blog
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Multimodal search: Searching with semantic and visual understanding
As we witness the evolution of ML models, like large language models (LLMs), imagine if they possessed a new dimension – the ability to comprehend images. Similar to the game-changing impact of LLMs in chatbots and text data, this new capability has the potential to revolutionize businesses by allowing ML models to decipher and categorize extensive image collections within enterprise...
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Configurable automation for OpenSearch ML use cases
In OpenSearch, to use machine learning (ML) offerings, such as semantic, hybrid, and multimodal search, you often have to grapple with complex setup and preprocessing tasks. Additionally, you must write verbose queries, which can be a time-consuming and error-prone process.
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OpenSearch 2.13 is ready for download!
OpenSearch 2.13 is live and available for download! The latest version of OpenSearch arrives with a range of machine learning (ML) tools to help you build AI-powered applications, along with upgrades that make it easier to access and analyze your operational data and new ways to enhance the resiliency of your OpenSearch clusters. To explore the release for yourself, visit...
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Using documentation for usability studies
Is your product usable? Are your users able to navigate it seamlessly? Do they find your UX options intuitive? This is what a usability study is designed to evaluate. In this blog post, we offer some best practices for running a usability study, including some essential tools.
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Enhanced multi-vector support for OpenSearch k-NN search with nested fields
In OpenSearch 2.12, users can now obtain diverse search results from a k-NN index, even when multiple nearest vectors belong to just a few documents. This is expected to enhance both the efficiency and quality of search outcomes.
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