Stability AI's Stable Diffusion 3.5 Large: Stability AI is a leading generative AI model developer in visual media, with cutting-edge models in image, video, 3D, and audio. Amazon Bedrock will soon add Stable Diffusion 3.5 Large, Stability AI's most advanced text-to-image model. This new model generates high-quality images from text descriptions in a wide range of styles to accelerate the creation of concept art, visual effects, and detailed product imagery for customers in media, gaming, advertising, and retail.
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.
Once a customer finds a model they want, they select the appropriate infrastructure for their scaling needs and easily deploy on AWS through fully managed endpoints. Customers can then securely integrate the model with Amazon Bedrock's unified application programming interfaces (APIs), leverage tools like Guardrails and Agents, and benefit from built-in security and privacy features.
Zendesk is a global service software company with a diverse and multicultural customer base of 100,000 brands around the world. The company can use specialized models, like Widn.AI for translation, in Amazon Bedrock to personalize and localize customer service requests across email, chat, phone, and social media. This will provide agents with the data they need, such as sentiment or intent in the customer's native language, to ultimately enhance the customer service experience.
Prompt caching and Intelligent Prompt Routing help customers tackle inference at scale
When selecting a model, developers need to balance multiple considerations, like accuracy, cost, and latency. Optimizing for any one of these factors can mean compromising on the others. To balance these considerations when deploying an application into production, customers employ a variety of techniques, like caching frequently used prompts or routing simple questions to smaller models. However, using these techniques is complex and time-consuming, requiring specialized expertise to iteratively test different approaches to ensure a good experience for end users. That is why AWS is adding two new capabilities to help customers more effectively manage prompts at scale.
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.
Amazon Bedrock 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.
Symbeo is a CorVel company that offers automated accounts payable solutions. The company will use Amazon Bedrock Data Automation to automate the extraction of data from complex documents, such as insurance claims, medical bills, and more. This will help Symbeo's teams process claims faster and accelerate the turnaround time to get back to their customers. Tenovos, a digital asset management platform, is using Amazon Bedrock Data Automation to enable semantic search at scale to increase content reuse by 50% or more, saving millions in marketing expenses.
Amazon Bedrock Marketplace is available today. Inference management capabilities, structured data retrieval and GraphRAG in Amazon Bedrock Knowledge Bases, and Amazon Bedrock Data Automation are all available in preview. Models from Luma AI, poolside, and Stability AI are coming soon.
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