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SpaceX
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NASA
СпутникиРНSpaceXРоскосмосNASAWe are excited to announce the general availability of Amazon Nova Multimodal Embeddings, a state-of-the-art embedding model for agentic RAG and semantic search, in AWS GovCloud (US-West). It is the first unified embedding model that supports text, documents, images, video, and audio through a single model, to enable cross-modal retrieval with leading accuracy.
Managing and searching across different content types traditionally required multiple specialized embedding models, leading to complexity, higher costs, and data silos. Amazon Nova Multimodal Embeddings maps diverse content types into a unified space with leading accuracy, helping break down these silos. Developers can build cross-modal applications that search video archives using complex queries, find relevant product images based on customer questions, or search financial documentation that contain both infographics and text explanations, all using a single embedding model.
The model supports inputs of up to 8K tokens in length and video/audio segments up to 30 seconds, with the capability to segment larger files. Multiple output embedding dimensions allow organizations to balance accuracy and performance with storage and computation costs. Organizations can choose between synchronous API for near real-time applications and asynchronous API for efficient processing of larger files, enabling them to optimize for both latency-sensitive and high-volume workloads.
To learn more, see the user guide. To get started with Nova Multimodal Embeddings in Amazon Bedrock, visit the Amazon Bedrock console in AWS GovCloud (US-West).
We are excited to announce the general availability of Amazon Nova Multimodal Embeddings, a state-of-the-art embedding model for agentic RAG and semantic search, in AWS GovCloud (US-West). It is the first unified embedding model that supports text, documents, images, video, and audio through a single model, to enable cross-modal retrieval with leading accuracy.
Managing and searching across different content types traditionally required multiple specialized embedding models, leading to complexity, higher costs, and data silos. Amazon Nova Multimodal Embeddings maps diverse content types into a unified space with leading accuracy, helping break down these silos. Developers can build cross-modal applications that search video archives using complex queries, find relevant product images based on customer questions, or search financial documentation that contain both infographics and text explanations, all using a single embedding model.
The model supports inputs of up to 8K tokens in length and video/audio segments up to 30 seconds, with the capability to segment larger files. Multiple output embedding dimensions allow organizations to balance accuracy and performance with storage and computation costs. Organizations can choose between synchronous API for near real-time applications and asynchronous API for efficient processing of larger files, enabling them to optimize for both latency-sensitive and high-volume workloads.
To learn more, see the user guide. To get started with Nova Multimodal Embeddings in Amazon Bedrock, visit the Amazon Bedrock console in AWS GovCloud (US-West).