Amazon Bedrock new innovations include more than 100 new models and powerful new capabilities for inference and working with data
AWS has announced new innovations for Amazon Bedrock, a fully managed service for building and scaling generative artificial intelligence (AI) applications with high-performing foundation models.
“Amazon Bedrock continues to see rapid growth as customers flock to the service for its broad selection of leading models, tools to easily customize with their data, built-in responsible AI features, and capabilities for developing sophisticated agents,” said Dr. Swami Sivasubramanian, Vice President of AI and Data at AWS. “Amazon Bedrock is helping to tackle the biggest roadblocks developers face today, so customers can realize the full potential of generative AI. With this new set of capabilities, we are empowering customers to develop more intelligent AI applications that will deliver greater value to their end users.”
The broadest selection of models from leading AI companies
Amazon Bedrock provides customers with the broadest selection of fully managed models from leading AI companies, including AI21 Labs, Anthropic, Cohere, Meta, Mistral AI, and Stability AI. Additionally, Amazon Bedrock is the only place customers can access the newly announced Amazon Nova models, a new generation of foundation models that deliver state-of-the-art intelligence across a wide range of tasks and industry-leading price performance. With today’s announcements, AWS is further expanding model choice in Amazon Bedrock with the addition of more industry-leading models.
Access more than 100 popular, emerging, and specialized models with Amazon Bedrock Marketplace
While the models in Amazon Bedrock can support a wide range of tasks, many customers want to incorporate emerging and specialized models into their applications to power unique use cases, like analyzing a financial document or generating novel proteins. With Amazon Bedrock Marketplace, customers can now easily find and choose from more than 100 models that can be deployed on AWS and accessed through a unified experience in Amazon Bedrock. This includes popular models such as Mistral AI’s Mistral NeMo Instruct 2407, Technology Innovation Institute’s Falcon RW 1B, and NVIDIA NIM microservices, along with a wide array of specialized models, including Writer’s Palmyra-Fin for the financial industry, Upstage’s Solar Pro for translation, Camb.ai’s text-to-audio MARS6, and EvolutionaryScale’s ESM3 generative model for biology.
Two new capabilities for Amazon Bedrock Knowledge Bases help customers maximize the value of their data
Customers want to leverage their data, no matter where, or in what format, it resides to build unique generative AI-powered experiences for end users. Knowledge Bases is a fully managed capability that makes it easy for customers to customize foundation model responses with contextual and relevant data using retrieval augmented generation (RAG). While Knowledge Bases already makes it easy to connect to data sources like Amazon OpenSearch Serverless and Amazon Aurora, many customers have other data sources and data types they would like to incorporate into their generative AI applications. That is why AWS is adding two new capabilities to Knowledge Bases.
Data Automation transforms unstructured multimodal data into structured data for generative AI and analytics
Today, most enterprise data is unstructured and is contained in content like documents, videos, images, and audio files. Many customers want to take advantage of this data to discover insights or build new experiences for customers, but it is often a difficult, manual process to convert it into a format that can be easily used for analytics or RAG. For example, a bank may take in multiple PDF documents for loan processing and need to extract details from each one, normalize features like name or date of birth for consistency, and transform the results into a text-based format before entering them into a data warehouse to perform any analyses. With Amazon Bedrock Data Automation, customers can automatically extract, transform, and generate data from unstructured content at scale using a single API.
Amazon Bedrock Data Automation can quickly and cost effectively extract information from documents, images, audio, and videos and transform it into structured formats for use cases like intelligent document processing, video analysis, and RAG. Amazon Bedrock Data Automation can generate content using predefined defaults, like scene-by-scene descriptions of video stills or audio transcripts, or customers can create an output based on their own data schema that they can then easily load into an existing database or data warehouse. Through an integration with Knowledge Bases, Amazon Bedrock Data Automation can also be used to parse content for RAG applications, improving the accuracy and relevancy of results by including information embedded in both images and text. Amazon Bedrock Data Automation provides customers with a confidence score and grounds its responses in the original content, helping to mitigate the risk of hallucinations and increasing transparency.
