New type of generative AI-powered assistant,
built with security and privacy in mind, empowers employees to get
answers to questions, solve problems, generate content, and take
actions using the data and expertise found at their company
Accenture, BMW Group, Gilead, Mission Cloud,
Orbit Irrigation, and Wunderkind among the customers and partners
excited to use Amazon Q
At AWS re:Invent, Amazon Web Services, Inc. (AWS), an
Amazon.com, Inc. company (NASDAQ: AMZN), today announced Amazon Q,
a new type of generative artificial intelligence-(AI) powered
assistant that is specifically for work and can be tailored to a
customer’s business. Customers can get fast, relevant answers to
pressing questions, generate content, and take actions—all informed
by a customer’s information repositories, code, and enterprise
systems. Amazon Q provides information and advice to employees to
streamline tasks, accelerate decision making and problem solving,
and help spark creativity and innovation at work. Designed to meet
enterprise customers’ stringent requirements, Amazon Q can
personalize its interactions to each individual user based on an
organization’s existing identities, roles, and permissions.
Additionally, Amazon Q never uses business customers’ content to
train its underlying models. Amazon Q brings generative AI-powered
assistance to customers building on AWS, working internally, and
using AWS applications for business intelligence (BI), contact
centers, and supply chain management to help organizations of all
sizes and across industries use generative AI safely. Amazon Q is
available to customers in preview, with Amazon Q in Connect
generally available and Amazon Q in AWS Supply Chain coming soon.
To learn more about Amazon Q, visit aws.amazon.com/q.
“Generative AI has the potential to spur a technological shift
that will reshape how people do everything from searching for
information and exploring new ideas to writing and building
applications,” said Dr. Swami Sivasubramanian, vice president of
Data and Artificial Intelligence. “AWS is helping customers harness
generative AI with solutions at all three layers of the stack,
including purpose-built infrastructure, tools, and applications.
Amazon Q builds on AWS’s history of taking complex, expensive
technologies and making them accessible to customers of all sizes
and technical abilities, with a data-first approach and
enterprise-grade security and privacy built-in from the start. By
bringing generative AI to where our customers work—whether they are
building on AWS, working with internal data and systems, or using a
range of data and business applications—Amazon Q is a powerful
addition to the application layer of our generative AI stack that
opens up new possibilities for every organization.”
Generative AI chat applications have captured the public’s
imagination and helped people understand what is possible, but
there are still barriers that prevent people from using these
solutions at work. Specifically, these chat applications do not
know an organization’s business, data, customers, operations, or
employees—the work they do, who they interact with, what
information they use, and what they can access. Additionally, these
solutions were not initially built with the security and privacy
features that organizations need for employees to safely use them
in their day-to-day work. This has led to companies adding these
features to their assistants after they were built, which does not
work as well as incorporating security into the assistant’s
fundamental design. That is why AWS created Amazon Q, helping
customers unlock the full benefit of generative AI for every
employee.
Amazon Q is an expert for customers building, deploying, and
operating applications and workloads on AWS
Today, developers and information technology (IT) professionals
are expected to keep up with the latest technological developments,
design and deliver new features quickly, manage the end-to-end
lifecycle of applications and workloads, and balance competing
priorities when it comes to building net-new capabilities and
maintaining existing offerings. All of this requires significant
work for developers and IT professionals that distracts them from
their core focus. Whether they are trying to answer a
straightforward question, like how a specific feature works, or a
nuanced one, like finding the best Amazon Elastic Compute Cloud
(Amazon EC2) instance for a given workload, customers spend a
significant portion of their time learning how things work through
documentation, public forums, and conversations with colleagues.
Once the application is up and running, customers need to dedicate
additional time and resources to maintain it. For example,
troubleshooting a network connectivity issue may require a customer
to work quickly to diagnose the problem, ensure there is proper
connectivity between resources, and review network configuration
details, sometimes in the absence of additional guidance or support
from teammates. In their integrated development environment (IDE),
a developer that takes over a project from a colleague may have to
spend time studying previously written code to understand its
underlying programming logic. Regardless of the project they are
working on, they also have to continuously debug, test, and
optimize their code, taking time away from building new features.
Throughout all of these steps, developers and IT professionals are
moving between the AWS Management Console and documentation, the
IDE, and chatrooms with colleagues, and there is not a unified
source to help answer questions across every step of the process
from planning to maintaining applications.
Trained on 17 years of AWS knowledge and experience, Amazon Q
transforms the way developers and IT professionals build, deploy,
and operate applications and workloads on AWS. Customers can access
Amazon Q through a conversational interface from the AWS Management
Console, documentation pages, their IDE, and over Slack or other
third-party chat apps. Amazon Q is an expert on patterns in the AWS
Well-Architected Framework, best practices, documentation, and
solution implementations, making it easier for customers to explore
new services and capabilities, get started faster, learn unfamiliar
technologies, architect solutions, troubleshoot, upgrade
applications, and more. Customers can get crisp answers and
guidance by asking questions to learn about AWS capabilities (e.g.,
“Tell me about Agents for Amazon Bedrock?”), research how an AWS
service works (e.g., “What are the scaling limits on a DynamoDB
table?”), figure out the best way to architect a solution (e.g.,
“What are the best practices for building event-driven
architectures?”), or identify the best service for their use case
(e.g., “What are the ways to build a web app on AWS?”). Based on
the question, Amazon Q will give succinct answers that include
citations and links to its sources, and customers can ask any
number of follow up questions to get more details, find the best
option for their workload, and receive an outline of the basic
steps to get started. Customers can also use Amazon Q to select the
best EC2 instance for their workload by asking questions like,
“Help me find the right EC2 instance to deploy a video encoding
workload for my gaming app with the highest performance,” and
Amazon Q will provide a list of instance families with the reasons
to use each of them. To troubleshoot an issue like an EC2 or Amazon
Simple Storage Service (Amazon S3) configuration error, customers
simply press the “Troubleshoot with Amazon Q” button while in the
AWS Management Console to have Amazon Q research the error and
suggest a fix. Customers can also troubleshoot network issues by
asking questions like, “Why can I not connect to my EC2 instance
from my laptop?” and Amazon Q will analyze a customer’s end-to-end
network configuration and provide a diagnosis (e.g., “This instance
appears to be in a private subnet, so public accessibility may need
to be established.”).
When accessed in the IDE via Amazon CodeWhisperer, Amazon Q
combines its expertise for building software with an understanding
of a customer’s code. Developers can use Amazon Q to explain
specific programming logic by asking questions (e.g., “Provide me
with a description of what this application does and how it
works.”), and Amazon Q will give details like which services the
code uses and what different functions do (e.g., “This application
is building a basic support ticketing system using Python Flask and
AWS Lambda.”), along with a description of the application’s core
capabilities, how they are implemented, and more. Amazon Q can also
help developers debug, test, and optimize their code. A developer
just needs to ask Amazon Q for help (e.g., “Optimize my selected
DynamoDB query), and Amazon Q provides a natural language
description of its suggestions along with the accompanying code a
developer can implement in one click.
Additionally, Amazon Q gives developers access to powerful
capabilities to solve common challenges, further simplifying
application development and maintenance, including:
- Develop features faster: If a developer wants to add a
new feature to an application today, they need to go through the
time-consuming process of mapping out a plan, thinking through the
programming logic, writing the code and tests, and integrating it
into the codebase, making small changes across potentially
thousands of lines of code. With the feature development
capability, developers can get guided assistance and automate much
of the end-to-end process. From Amazon CodeCatalyst, AWS’s unified
software development service for teams, a developer assigns Amazon
Q a backlog task from their issues list, and Amazon Q then drafts a
step-by-step plan, writes the code, and presents a developer with
the suggested changes to implement the feature—a developer only
needs to review the suggestions, make any necessary adjustments,
approve the update, and deploy it.
- Amazon Q Code Transformation: Many developers today
spend hours on application maintenance and upgrades, leaving less
time for writing code or building new applications. While these
upgrades can be important for application security and performance
improvement, they often require months or years for developers to
go through every line of code making updates. With Amazon Q Code
Transformation, developers can remove a lot of the heavy lifting of
this process, reducing the time required from days to minutes. A
developer just opens the code they want to transform in their IDE
and asks Amazon Q to “/transform” it. Amazon Q then analyzes the
codebase, identifies and updates its dependencies, generates the
new code language, incorporates the latest security and performance
enhancements, and tests to validate the application will run.
Recently, a small team of five Amazon developers used Amazon Q Code
Transformation to upgrade 1,000 production applications from Java 8
to Java 17 in just two days. The average time per application was
less than 10 minutes. Amazon Q Code Transformation currently
supports language upgrades from Java 8 to Java 17, and .NET
Framework to cross-platform .NET upgrades coming soon, with even
more transformations to follow in the future.
Amazon Q is an expert on a customer’s business
Organizations are sitting on vast amounts of information spread
across multiple documents, systems, and applications. From finance
and human resources to marketing and sales, employees across every
organization collectively spend hours every week searching internal
sources for information, piecing together analyses, writing
reports, building presentations, or adapting content for different
customers or audiences. Generative AI can help solve these
challenges, but the general-purpose solutions available today are
not connected to internal resources and do not understand a
company’s existing identities, roles, and permissions to determine
which resources an employee should have access to for their work.
Publicly available solutions may also use data inputs and outputs
for training, opening companies up to security and privacy risks,
which has led to some organizations banning these offerings. While
there are some generative AI solutions designed to work with a
specific set of productivity tools, they only work within those
tools and do not extend across all of an organization’s systems and
applications. Because of these barriers, employees have been unable
to tap into the full potential of generative AI.
Customers can connect Amazon Q to their business data,
information, and systems, so it can synthesize everything and
provide tailored assistance to help employees solve problems,
generate content, and take actions relevant to their business. With
more than 40 built-in connectors for popular data sources,
including Amazon S3, Dropbox, Confluence, Google Drive, Microsoft
365, Salesforce, ServiceNow, and Zendesk, as well as the option to
build custom connectors for internal intranets, wikis, run books,
and more, Amazon Q makes it fast and easy for customers to get
started. Once Amazon Q synthesizes all the information it’s
connected to and a customer is ready to deploy their own assistant,
Amazon Q generates a web application that employees can access
using a customer’s existing authentication system. Amazon Q uses
the authentication system to understand a user, their role, and
what systems they are permitted to access, so employees can ask
detailed, nuanced questions and get tailored results that only
include information that the user has access to view. Employees can
ask Amazon Q about anything they would have to historically search
for across different data sources (e.g., “What are the latest
guidelines for logo usage?”), and Amazon Q will synthesize the
relevant content, sharing answers and links to sources. Amazon Q
can also streamline day-to-day communications, helping employees
with tasks like generating a blog post, summarizing documents,
drafting emails, and creating meeting agendas. Employees can also
use Amazon Q to complete tasks in popular systems like Jira,
Salesforce, ServiceNow, and Zendesk. For example, an employee could
ask Amazon Q to open a ticket in Jira or create a case in
Salesforce.
Amazon Q provides answers and insights that are accurate and
faithful to the source material and knowledge a customer provides
it, and customers can use additional administrative controls to
block entire topics and filter both questions and finalized answers
using keywords. Administrators can also limit certain responses to
specific employees or data sources. For example, Amazon Q can be
set to only respond to security-related questions from the security
team or pull answers to people-related questions from a company’s
internal directory.
Amazon Q provides generative AI-powered assistance across
Amazon QuickSight, Amazon Connect, and AWS Supply Chain
While many use cases and industries will benefit from the
transformative potential of generative AI, the solutions available
today are often generic and do not have the specific context needed
to carry out domain-specific tasks. To unlock the full benefit of
generative AI, customers need access to purpose-built solutions
adapted to the nuances of their use case or industry. That is why
AWS is bringing Amazon Q to multiple services and applications,
including:
- Amazon Q is in Amazon QuickSight (preview): Amazon
QuickSight is a unified BI service built for the cloud that offers
interactive dashboards, paginated reports, and embedded analytics,
plus natural-language querying capabilities. With Amazon Q in
QuickSight, customers can access generative AI-powered capabilities
to build dashboards and more easily use existing dashboards to
simplify decision making using data stories, inform business
stakeholders of changes, and distill key insights. With the new
story generation feature, users can ask Amazon Q to “build a story
about how the business has changed over the last month for a
business review with leadership.” In seconds, Amazon Q creates a
data-driven, visually compelling story based on the available data
in QuickSight that users can further customize and share throughout
their organization. Additionally, with new executive summaries on
dashboards and reports, Amazon Q creates at-a-glance summaries that
highlight what is important to pay attention to in a dashboard.
Business users can also use a new, streamlined
question-and-answering experience where they can ask exploratory
questions and generate relevant answers not limited to the visuals
in their dashboards and reports. For example, a user could ask,
“Why did the number of orders increase last month?” and Amazon Q
would summarize the details in a dashboard created on the fly with
supporting visuals.
- Amazon Q is in Amazon Connect (generally available):
Amazon Connect is the cloud contact center that enables
organizations of all sizes to deliver superior customer experiences
at lower cost. Contact center agents play a critical role in
helping organizations build customer trust and loyalty by guiding
customers through complex decisions, but it is challenging to
onboard, train, and coach employees to become high performers and
ensure they have the information they need to respond to customers
quickly and accurately. Amazon Q in Connect detects customer issues
based on the real-time conversation between the customer and agent,
and automatically provides the agent responses, suggested actions,
and links to relevant articles. By empowering agents to address
customer needs across a broad range of topics without assistance
from supervisors, Amazon Q in Connect increases customer
satisfaction while reducing agent training, resolution time, and
cost. For example, Amazon Q could detect a customer is contacting a
rental car company to change their reservation. Amazon Q would then
generate a response the agent could send detailing the company’s
change policies and guide the agent through the step-by-step
process of updating the reservation. To learn more about Amazon Q
in Connect, see the Amazon Connect press release.
- Amazon Q is in AWS Supply Chain (coming soon): AWS
Supply Chain is a cloud-based application that gives customers
insights into their supply chain by combining Amazon’s nearly 30
years of supply chain experience with the resilience, security, and
business continuity of AWS. Many customers are looking for a more
intuitive way to understand how inventory changes upstream and
downstream could impact their future operations. With Amazon Q in
AWS Supply Chain, customers will be able to ask “what,” “why,” and
“what if” questions about their supply chain data, visualize
outcomes of complex scenarios, and ask follow-up questions to
understand the tradeoffs between different decisions. For example,
a customer could ask “What is causing the delay in my shipments and
how can I speed things up?” and Amazon Q could provide an analysis
of a customer’s supply chain that notes most of the orders were on
the East Coast, a storm caused a delay, and they could expedite
their deliveries and reduce costs by shipping to New York instead
of Miami. To learn more about Amazon Q in AWS Supply Chain, see the
AWS Supply Chain press release.
Accenture, an AWS Premier Tier Services Partner, is a leading
global professional services company with resources focused on
accelerating end-to-end adoption of AWS and maximizing
enterprise-wide transformation, securely, at speed and scale.
“Amazon Q will be transformational for Accenture as we continue to
work closely alongside AWS to accelerate the adoption and
deployment of generative AI technologies amongst our own engineers
and with organizations around the world,” said Karthik Narain,
group chief executive at Accenture. “Our latest research shows
nearly all C-suite executives expect generative AI to be
transformative for their company and their industry, so we are
investing now to get ahead of the curve by enabling up to 50,000 of
our software developers and IT professionals with Amazon
CodeWhisperer and Amazon Q over the next two years. With Amazon
CodeWhisperer, we have already seen a 30% boost in development,
while also improving security, quality, and performance, and we
expect that will only grow as we roll out Amazon Q across our
organization.”
BMW Group is a German multinational manufacturer of luxury
vehicles and motorcycles. “BMW teams need to ingest and interpret
new data quickly to deliver the precision experiences our customers
expect,” said Christoph Albrecht, data engineering and analytics
consultant at BMW Group. “New Amazon Q capabilities in QuickSight
help our analysts build dashboards in hours when it used to take
days. We are seeing an even greater impact with our business users,
where Amazon Q in QuickSight is accelerating critical business
decisions at the highest levels of our organization by enabling
on-the-fly answers to time-critical questions. The stories feature
also enables us to present a clear picture of the business for
board meetings, building insightful, professionally formatted
stories fast. Amazon Q in QuickSight is the high-performance fuel
our demanding teams consume to get precision answers fast."
Gilead Sciences, Inc. is a biopharmaceutical company that has
pursued and achieved breakthroughs in medicine for more than three
decades, with the goal of creating a healthier world for all
people. “Gilead's use of generative AI on AWS has led to faster
innovation and productivity gains,” said Kevin Cox, chief cloud
architect at Gilead. “By leveraging Amazon Q, we can generate
insights and accelerate analysis of large amounts of data across
our enterprise. Overall, Amazon Q provides a faster way to create
generative AI solutions by streamlining connections to our data
sources, automating complex tasks, such as managing vector stores,
and quickly surfacing relevant insights on demand. For life
sciences organizations like Gilead, the productivity benefits
unlocked by generative AI solutions on AWS like Amazon Q are
exciting.”
Mission Cloud is an AWS Premier Services Partner that empowers
businesses to invent a greater future in the cloud by leveraging
the leading cloud platform. “Our team of cloud experts regularly
works with the breadth and depth of AWS technologies to help
customers manage, modernize, and optimize their cloud environments
or build entirely new applications,” said Jonathan LaCour, CTO at
Mission Cloud. “While AWS gives us the infrastructure, tools, and
services we need to delight our clients, there is still a lot of
undifferentiated work in the software development process outside
of working with AWS services. With capabilities to automate new
feature development, remediate errors, and even upgrade
applications, Amazon Q will give our developers time to focus on
adding even more value to the work we do with clients. Long-term
projects to upgrade applications will likely shrink to days, and we
can accelerate shipping new features when managing legacy
applications, despite starting with no prior documentation or
guides. Amazon Q will help us more efficiently build, deploy, and
operate workloads on AWS for our customers.”
Orbit Irrigation is a manufacturer and supplier of home and
commercial irrigation systems. “In order to resolve customers’
questions, our agents spend 2-3 minutes per interaction searching
through several different sources of knowledge, including Orbit
product pages, customer account pages, and internal knowledge
forums,” said Brian Dick, senior manager of Customer Care at Orbit
Irrigation. “This multistep process adds time to the interactions
for agents and customers. The new responses automatically generated
at each turn of the customer conversation by Amazon Q in Connect
are tailored based on our own knowledge base articles. Amazon Q in
Connect will create 10%-15% time savings on every contact, and the
increased number of calls handled every hour is expected to
translate directly into costs savings for Orbit—all done with more
resolved customer questions and higher customer satisfaction.”
Wunderkind is a leading digital marketing platform that delivers
performance marketing and advertising solutions to brands,
publishers, and advertisers. “We have an unbelievable amount of
proprietary data, but it is difficult looking across our multiple
data silos to find the right answer and distill the information
into quick, actionable insights,” said Richard Jones, chief revenue
officer at Wunderkind. “Adding Amazon Q as a topline layer over our
various content and data repositories brings a whole new level of
efficiency to our customer success and marketing teams. Based on
initial estimates, we expect the time spent on content discovery
alone to be reduced by over 30%, which empowers our success team to
service clients faster, and with better accuracy. It also
jumpstarts the creation of sales and marketing content, such as
email drips, whitepapers, and ad copy. With Amazon Q, we anticipate
the ability to accelerate the content creation process by nearly
50%, allowing us to shift our attention to scaling the
personalization of content instead of spending time on the
laborious task of creating materials from scratch.“
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, virtual and augmented reality (VR and AR), media, and
application development, deployment, and management from 102
Availability Zones within 32 geographic regions, with announced
plans for 15 more Availability Zones and five more AWS Regions in
Canada, Germany, Malaysia, New Zealand, and Thailand. 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.
View source
version on businesswire.com: https://www.businesswire.com/news/home/20231128307286/en/
Amazon.com, Inc. Media Hotline Amazon-pr@amazon.com
www.amazon.com/pr Source: Amazon Web Services, Inc.
Amazon.com (NASDAQ:AMZN)
Historical Stock Chart
From Jun 2024 to Jul 2024
Amazon.com (NASDAQ:AMZN)
Historical Stock Chart
From Jul 2023 to Jul 2024