The biggest expansion of models to date, new
inference optimization tools, and additional data capabilities give
customers even greater flexibility and control to build and deploy
production-ready generative AI faster
At AWS re:Invent, Amazon Web Services, Inc. (AWS), an
Amazon.com, Inc. company (NASDAQ: AMZN), today announced new
innovations for Amazon Bedrock, a fully managed service for
building and scaling generative artificial intelligence (AI)
applications with high-performing foundation models. Today’s
announcements reinforce AWS’s commitment to model choice, optimize
how inference is done at scale, and help customers get more from
their data.
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the full release here:
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Discover Amazon Bedrock Marketplace
models and Amazon Bedrock fully managed models in the new model
catalog (Graphic: Business Wire)
- AWS will soon be the first cloud provider to offer models from
Luma AI and poolside. AWS will also add the latest Stability AI
model in Amazon Bedrock and, through the new Amazon Bedrock
Marketplace capability, is giving access to more than 100 popular,
emerging, and specialized models, so customers can find the right
set of models for their use case.
- New prompt caching and Amazon Bedrock Intelligent Prompt
Routing help customers more easily and cost effectively scale
inference.
- Support for structured data and GraphRAG in Amazon Bedrock
Knowledge Bases further expands how customers can leverage their
data to deliver customized generative AI experiences.
- Amazon Bedrock Data Automation automatically transforms
unstructured, multimodal data into structured data with no coding
required—helping customers use more of their data for generative AI
and analytics.
- Tens of thousands of customers trust Amazon Bedrock to run
their generative AI applications as the service has grown its
customer base by 4.7x in the last year. Adobe, Argo Labs, BMW
Group, Octus, Symbeo, Tenovos, and Zendesk are already adopting the
latest Amazon Bedrock advancements.
“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.
- Luma AI’s Ray 2: Luma AI’s multimodal models and
software products advance video content creation with generative
AI. AWS will be the first cloud provider to make Luma AI’s
state-of-the-art Luma Ray 2 model, the second generation of its
renowned video model, available to customers. Ray 2 marks a
significant advancement in generative AI-assisted video creation,
generating high-quality, realistic videos from text and images with
efficiency and cinematographic quality. Customers can rapidly
experiment with different camera angles and styles, create videos
with consistent characters and accurate physics, and deliver
creative outputs for architecture, fashion, film, graphic design,
and music.
- poolside’s malibu and point: poolside addresses the
challenges of modern software engineering for large enterprises.
AWS will be the first cloud provider to offer access to poolside’s
malibu and point models, which excel at code generation, testing,
documentation, and real-time code completion. This empowers
engineering teams to improve productivity, write better code
faster, and accelerate product development cycles. Both models can
also be fine-tuned securely and privately on customers’ codebases,
practices, and documentation, enabling them to adapt to specific
projects and helping customers tackle daily software engineering
tasks with increased accuracy and efficiency. Additionally, AWS
will be the first cloud provider to offer access to poolside’s
Assistant, which puts the power of poolside’s malibu and point
models inside of developers' preferred integrated development
environments (IDEs).
- 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.
- Lower response latency and costs by caching prompts:
Amazon Bedrock can now securely cache prompts to reduce repeated
processing, without compromising on accuracy. This can reduce costs
by up to 90% and latency by up to 85% for supported models. For
example, a law firm could create a generative AI chat application
that can answer lawyers’ questions about documents. When multiple
lawyers ask questions about the same part of a document in their
prompts, Amazon Bedrock could cache that section, so the section
only gets processed once and can be reused each time someone wants
to ask a question about it. This reduces the cost by shrinking the
amount of information the model needs to process each time. Adobe’s
Acrobat AI Assistant enhances user productivity by enabling quick
document summarization and question answering. With prompt caching
on Amazon Bedrock, Adobe observed a 72% reduction in response time,
based on preliminary testing.
- Intelligent Prompt Routing helps optimize response quality
and cost: With Intelligent Prompt Routing, customers can
configure Amazon Bedrock to automatically route prompts to
different foundation models within a model family, helping them
optimize for response quality and cost. Using advanced prompt
matching and model understanding techniques, Intelligent Prompt
Routing predicts the performance of each model for each request and
dynamically routes requests to the model most likely to give the
desired response at the lowest cost. Intelligent Prompt Routing can
reduce costs by up to 30% without compromising on accuracy. Argo
Labs, which delivers innovative voice agent solutions for
restaurants, handles diverse customer inquiries and reservations
with Intelligent Prompt Routing. As customers submit questions,
place orders, and book tables, Argo Labs’ voice chatbot dynamically
routes the query to the most suitable model, optimizing for both
cost and quality of responses. For example, a simple yes-no
question, like “Do you have an open table at this restaurant
tonight?” could be handled by a smaller model, while a larger model
could answer more complex questions such as, “What kind of vegan
options does this restaurant provide?” With Intelligent Prompt
Routing, Argo Labs can use their voice agents to seamlessly handle
customer interactions, while achieving the right balance of
accuracy and cost.
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.
- Support for structured data retrieval accelerates generative
AI app development: Knowledge Bases provides one of the first
managed, out-of-the-box RAG solutions that enables customers to
natively query their structured data where it resides for their
generative AI applications. This capability helps break data silos
across data sources, accelerating generative AI development from
over a month to just days. Customers can build applications that
use natural language queries to explore structured data stored in
sources like Amazon SageMaker Lakehouse, Amazon S3 data lakes, and
Amazon Redshift. With this new capability, prompts are translated
into SQL queries to retrieve data results. Knowledge Bases
automatically adjusts to a customer’s schema and data, learns from
query patterns, and provides a range of customization options to
further enhance the accuracy of their chosen use case. Octus, a
credit intelligence company, will use the new structured data
retrieval capability in Knowledge Bases to allow end users to query
structured data using natural language. By connecting Knowledge
Bases to Octus’ existing master data management system, end-user
prompts can be translated into SQL queries that Amazon Bedrock uses
to retrieve the relevant information and return it to the user as
part of the application’s response. This will help Octus’ chatbots
deliver precise, data-driven insights to its users and enhance the
users’ interactions with the company’s array of data products.
- Support for GraphRAG generates more relevant responses:
Knowledge graphs allow customers to model and store relationships
between data by mapping different pieces of relevant information
like a web. These knowledge graphs can be particularly useful when
incorporated into RAG, allowing a system to easily traverse and
retrieve relevant parts of information by following the graph. Now,
with support for GraphRAG, Knowledge Bases can enable customers to
automatically generate graphs using Amazon Neptune, AWS’s managed
graph database, and link relationships between entities across
data, without requiring any graph expertise. Knowledge Bases makes
it easier to generate more accurate and relevant responses,
identify related connections using the knowledge graph, and view
the source information to understand how a model arrived at a
specific response. BMW Group will implement GraphRAG for My AI
Assistant (MAIA), an AI-powered virtual assistant that helps users
find, understand, and integrate the company’s internal data assets
hosted on AWS. With GraphRAG’s automated graph modeling powered by
Amazon Neptune, BMW will be able to continuously update the
knowledge graph powering MAIA based on data usage to provide more
relevant and comprehensive insights from its data assets to
continue creating premium experiences for millions of drivers.
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.
To learn more, visit:
- The AWS News Blog for details on today’s announcements: Amazon
Bedrock Marketplace, prompt caching and Intelligent Prompt Routing,
and data processing and retrieval capabilities.
- The Amazon Bedrock page to learn more about the
capabilities.
- The Amazon Bedrock customer page to learn how companies are
using Amazon Bedrock.
- The AWS re:Invent page for more details on everything happening
at AWS re:Invent.
About Amazon Web Services
Since 2006, Amazon Web Services has been the world’s most
comprehensive and broadly adopted cloud. AWS has been continually
expanding its services to support virtually any workload, and it
now has more than 240 fully featured services for compute, storage,
databases, networking, analytics, machine learning and artificial
intelligence (AI), Internet of Things (IoT), mobile, security,
hybrid, media, and application development, deployment, and
management from 108 Availability Zones within 34 geographic
regions, with announced plans for 18 more Availability Zones and
six more AWS Regions in Mexico, New Zealand, the Kingdom of Saudi
Arabia, Taiwan, Thailand, and the AWS European Sovereign Cloud.
Millions of customers—including the fastest-growing startups,
largest enterprises, and leading government agencies—trust AWS to
power their infrastructure, become more agile, and lower costs. To
learn more about AWS, visit aws.amazon.com.
About Amazon
Amazon is guided by four principles: customer obsession rather
than competitor focus, passion for invention, commitment to
operational excellence, and long-term thinking. Amazon strives to
be Earth’s Most Customer-Centric Company, Earth’s Best Employer,
and Earth’s Safest Place to Work. Customer reviews, 1-Click
shopping, personalized recommendations, Prime, Fulfillment by
Amazon, AWS, Kindle Direct Publishing, Kindle, Career Choice, Fire
tablets, Fire TV, Amazon Echo, Alexa, Just Walk Out technology,
Amazon Studios, and The Climate Pledge are some of the things
pioneered by Amazon. For more information, visit amazon.com/about
and follow @AmazonNews.
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