Today, Amazon Web Services, Inc. (AWS) shared that tens of thousands of customers are using AWS machine
learning services, with active users increasing more than 250 percent in
the last year, spurred by the broad adoption of Amazon SageMaker since
AWS re: Invent 2017. Amazon SageMaker is a fully managed service that
removes the heavy lifting, complexity, and guesswork from each step of
the machine learning process, empowering everyday developers and
scientists to use machine learning much more expansively and
successfully. AWS has meaningfully more reference customers for machine
learning than any other provider, and much of it has to do with AWS's
unmatched array of services that enable a full stack machine learning
experience. With AWS machine learning services, customers are building a
wide variety of intelligent applications and solutions with the help of
AWS's P2 and P3 graphical processing unit (GPU) instances, deep learning
Amazon Machine Images (AMIs) that embed all the major frameworks, Amazon
SageMaker, AWS DeepLens-a device that has helped thousands of customers
gain hands on experience with machine learning, and services at the top
layer of the stack such as Amazon Rekognition, Amazon Polly, Amazon Lex,
and Amazon Comprehend.
Today, AWS also announced the general availability of two new machine
learning services, which are part of AWS's machine learning portfolio,
Amazon Transcribe and Amazon Translate. Amazon Transcribe provides
grammatically correct transcriptions of audio files to allow audio data
to be analyzed, indexed, and searched. Amazon Translate is a deep
learning powered machine translation service that provides natural
sounding language translation in both real-time and batch scenarios.
These services further extend the language capabilities already provided
on AWS with Amazon Lex for conversational interfaces, Amazon Polly for
Text-to-Speech, and Amazon Comprehend for processing natural language to
discover insights and contextual relationships in text.
"A lot of companies are talking about the potential of machine learning
and artificial intelligence, and thinking about how to incorporate these
technologies in their applications, but in reality, machine learning has
been out of reach for all but the few organizations who have expert
practitioners and data scientists on staff," said Swami Sivasubramanian,
Vice President of Machine Learning at AWS. "AWS changed all this with
the introduction of Amazon SageMaker that makes machine learning
accessible to everyday developers by eliminating the heavy lifting of
building, training, and deploying models."
Sivasubramanian continued, "More companies are doing machine learning on
AWS than anywhere else-at every layer of the stack. From those who are
super comfortable with machine learning using their favorite frameworks
with our high performance P3 instances, to everyday developers
incorporating machine learning into their applications for the first
time using Amazon SageMaker, to developers leveraging voice, text,
video, translation, facial recognition, and audio transcription to
invent new customer experiences using AWS's artificial intelligence
services."
Articulate, Cathay Pacific, Cerner, Cookpad, Cox Automotive, DailyLook,
DigitalGlobe, Dow Jones, Echo360, Edmunds.com, Enetpulse, Expedia.com,
FamilySearch, FICO, GE Healthcare, Genesys, Grammarly, Intuit, KloudGin,
Lau Brothers, Limbik, Lionbridge, NFL, One Hour Translation,
Polotico.eu, POPSUGAR, PubNub, Realtor.com, RedAwning.com, Shutterfly,
TINT, Tinder, VidMob, VMWare, and ZipRecruiter are just a few of the
tens of thousands of customers using AWS machine learning technologies
to reimagine customer experiences and innovate across their businesses.
Harnessing data and analytics across hardware, software, and biotech, GE
Healthcare is transforming healthcare by delivering better outcomes for
providers and patients. "Amazon SageMaker allows GE Healthcare to access
powerful artificial intelligence tools and services to advance improved
patient care," said Sharath Pasupunuti, Artificial Intelligence
Engineering Leader at GE Healthcare. "The scalability of Amazon
SageMaker, and its ability to integrate with native AWS services, adds
enormous value for us. We are excited about how our continued
collaboration between the GE Health Cloud and Amazon SageMaker will
drive better outcomes for our healthcare provider partners and deliver
improved patient care."
An early enterprise AWS customer, Intuit is a financial technology
company that is committed to powering prosperity around the world for
consumers, small businesses, and the self-employed through its ecosystem
of global products and platforms. "By including AWS machine learning and
artificial intelligence workloads in our overall artificial intelligence
and machine learning strategy, we can accelerate the end-user benefits
within our flagship products like QuickBooks, Mint, and TurboTax," said
H. Tayloe Stansbury, Intuit's Executive Vice President and Chief
Technology Officer. "Intuit started our artificial intelligence journey
over ten years ago and are proud that we have over 150 patents and 40
systems in production in this area, and we look forward to continue
innovating to delight our customers."
Edmunds.com is a car-shopping website that offers detailed, constantly
updated information about vehicles to 20 million monthly visitors. "We
have a strategic initiative to put machine learning into the hands of
all our engineers," said Stephen Felisan, Chief Information Officer at
Edmunds.com. "Amazon SageMaker is key to helping us achieve this goal,
making it easier for engineers to build, train, and deploy machine
learning models and algorithms at scale. We are excited to see how we
can use Amazon SageMaker to innovate new solutions across the
organization for our customers."
The Move, Inc. network, which includes Realtor.com,
Doorsteps, and Moving.com, provides
real estate information, tools, and professional expertise across a
family of websites and mobile experiences for consumers and real estate
professionals. "We believe that Amazon SageMaker is a transformative
addition to the realtor.com toolset
as we support consumers along their homeownership journey," said Vineet
Singh, Chief Data Officer and Senior Vice President at Move, Inc.
"Machine learning workflows that have historically taken a long time,
like training and optimizing models, can be done with greater efficiency
and by a broader set of developers, empowering our data scientists and
analysts to focus on creating the richest experience for our users."
Dow Jones is a publishing and financial information firm that publishes
the world's most trusted business news and financial information in a
variety of media. It delivers breaking news, exclusive insights, expert
commentary and personal finance strategies. "As Dow Jones continues to
focus on integrating machine learning into our products and services,
AWS has been a great resource," said Ramin Beheshti, Group Chief Product
and Technology Officer. "Leading up to our recent Machine Learning
Hackathon, the AWS team provided training to participants on Amazon
SageMaker and Amazon Rekognition, and offered day-of support to all the
teams. The result was that our teams developed some great ideas for how
we can apply machine learning, many of which we we'll continue to
develop on AWS. The event was a huge success, and an example of what a
great relationship can look like."
Every day Grammarly's algorithms help millions of people communicate
more effectively by offering writing assistance on multiple platforms
across devices. Through a combination of natural language processing and
advanced machine learning technologies, Grammarly is tackling critical
communication and business challenges. "Amazon SageMaker makes it
possible for us to develop our TensorFlow models in a distributed
training environment," said Stanislav Levental, Technical Lead at
Grammarly. "Our workflows also integrate with Amazon EMR for
pre-processing, so we can get our data from Amazon Simple Storage
Service (Amazon S3), filtered with Amazon EMR and Spark from a Jupyter
notebook, and then train in Amazon SageMaker with the same notebook.
Amazon SageMaker is also flexible for our different production
requirements. We can run inferences on Amazon SageMaker itself, or if we
need just the model, we download it from Amazon S3 and run inferences of
our mobile device implementations for iOS and Android customers."
Cookpad is Japan's largest recipe sharing service, with about 60 million
monthly users in Japan and about 90 million monthly users globally.
"With the increasing demand for easier use of Cookpad's recipe service,
our data scientists will be building more machine learning models in
order to optimize the user experience," said Mr. Yoichiro Someya,
Research Engineer at Cookpad. "Attempting to minimize the number of
training job iterations for best performance, we recognized a
significant challenge in the deployment of machine learning inference
endpoints, which was slowing down our development processes. To automate
the machine learning model deployment such that data scientists could
deploy models by themselves, we used Amazon SageMaker inference APIs and
proved that Amazon SageMaker would eliminate the need for application
engineers to deploy machine learning models. We anticipate automating
this process with Amazon SageMaker in production."
Echo360 provides leading video platform technology that helps
instructors and students record, stream, manage, and share interactive
video to improve student engagement before, during, and after class.
"The Echo360 platform fosters active and engaging video-based learning
that serves today's student," said Fred Singer, Chief Executive Officer
of Echo360. "We're excited about Amazon Transcribe because it offers our
university partners high-quality transcripts for each video, enabling
more powerful search, lower cost captioning of educational video
content, and enhanced note-taking, making learning assets more valuable
and accessible to students."
PubNub is the leading provider of real-time APIs for building chat,
device control, and real-time mapping apps. "At PubNub, we've found that
chat and collaboration has emerged as a dominant use case across our
global customer base, with increasing demand for multilingual user
experiences," said David Hegarty, Director of Product Management,
PubNub. "We are excited to bring the innovative power of Amazon
Translate to PubNub ChatEngineTM, a complete framework for chat and
serverless deployment. Combined with other artificial intelligence
offerings like Amazon Polly (text-to-speech) and Amazon Lex (chatbots),
this will help make chat apps smarter and ultimately make it easier for
our customers to grow their businesses internationally through
high-performance and localized chat functionality."
One Hour Translation is one of the world's largest online translation
agencies, offering professional translation services to thousands of
business customers worldwide, 24/7/365. "Using our services and
technology, global companies can localize massive amounts of content
quickly while maintaining high quality," said Ofer Shoshan, Chief
Executive Officer of One Hour Translation. "We're excited about the
initial results we've seen with Amazon Translate on a translation
project we ran for iHerb. The translation time was cut by 67 percent,
while maintaining the same quality standards that we hold. By running
human post-editing on the neural machine translations, there is
substantial cost reduction, as well as speed improvement benefits to be
realized for high volume translation projects."
The Customer Communication Services (CCS) team at FICO helps banks,
telecommunications, and utilities around the world connect more
effectively with their consumers using analytically-driven, intelligent,
automated channels. "Using the Amazon Polly Text-to-Speech service, we
can now create and edit voice responses in seconds versus days," said
Simon Woollett, Vice President of CCS at FICO. "This innovation has made
us more agile and responsive to the needs of our customers. We are now
able to generate speech recordings for our interactive voice response
systems and voice notification products at speed, which is essential for
our customer organizations who are working in dynamic and highly
regulated markets. Plus, we can do this across dozens of languages
helping us enter new markets and simplifying what would otherwise be a
difficult and expensive exercise recording live talent."
Articulate is the creator of award-winning Articulate 360, a
subscription that includes Storyline 360 and Rise, which are
applications that make it simple to create beautiful, engaging
e-learning that works on every device. "Our goal is to make every aspect
of e-learning course development easier, faster, and less expensive,"
said Mike Olivieri, Senior Vice President of Engineering at Articulate.
"With the integrated text-to-speech feature powered by Amazon Polly,
Articulate Storyline 360 users can generate narration for their
e-learning courses very quickly. Amazon Polly makes it extremely easy to
switch out languages and voices to localize Articulate Storyline 360
courses and make sure every word sounds the way it should."
POLITICO is a global news and information company with one of the most
robust and rapidly expanding rosters of journalists covering politics
and policy in the world. "Today's readers access content in a variety of
ways-online, print, and voice," said Johannes Boege, Chief Product
Officer at POLITICO in Europe. "At POLITICO, we are focused on meeting
readers wherever they are. By quickly integrating the Amazon Polly
Plugin for WordPress from AWS and WP Engine, we're able to deliver
content across additional channels for broader consumption and to
provide better accessibility to our news."
With 20 billion matches to date, Tinder is the world's most popular app
for meeting new people. "Behind every Tinder swipe is a system that
manages millions of requests a minute, billions of swipes a day, across
more than 190 countries," said Elie Seidman, Chief Executive Officer of
Tinder. "Amazon SageMaker simplifies machine learning, helping our
development teams to build models for predictions that create new
connections that otherwise might have never been possible."
POPSUGAR Inc. is a global media and technology company that delivers
multi-platform content to a global audience of over 400 million. With an
average of 3.1 billion global monthly content views in 2017, POPSUGAR
sought to take away the pains of manually tagging photos and begin
leveraging machine learning automation at a low cost. "We use Amazon
Rekognition to identify celebrities in our huge digital asset library,"
said Bjorn Pave, Senior Director of IT at POPSUGAR. "Amazon Rekognition
enabled us to stop manually tagging thousands of photos and provides us
with much needed automation for our ever-growing library."
KloudGin delivers an AI-based intelligent field service, asset, and
inventory management solution running on AWS. Through a single
application, KloudGin connects customers, crews, back office, partners,
and equipment in real time, from any device. "Amazon Lex wires into
KloudGin's Cloud Platform, allowing us to address the single primary
issue that plagues enterprise business customers-user adoption. Amazon
Lex is helping our customers interact with KloudGin using their natural
voice, similar to asking questions or taking actions in real world
conversations," said Vikram Takru, Founder and Chief Executive Officer
of KloudGin.
RedAwning.com is the world's largest branded network of vacation rental
properties. "RedAwning serves tens of thousands of vacation rental
guests each month and Amazon Connect with Amazon Lex has helped us serve
guests faster and more efficiently for both RedAwning and our guests,"
says Tim Choate, Founder and Chief Executive Officer of RedAwning.com.
"With Amazon Connect, we now have ten times the functionality for a
tenth of the cost, and we no longer have expensive per agent license
costs, nor the complexity of having to manage telephony. Using Amazon
Lex, we built a virtual assistant, ‘Scarlett,' and integrated it with
Amazon Connect. The virtual assistant takes advantage of the text to
speech functionality of Amazon Lex along with automatic speech
recognition. We also use AWS Lambda for back-office data base
integration, to quickly match customers to their reservations by phone
number and help them resolve the most frequent call-center queries
completely and faster, without the need for a human touch. This is
especially important as we are growing our customer base rapidly."
TINT helps B2C marketers find, curate, and display their most effective
customer generated content from social media in their marketing. "Our
business is focused on delivering the best marketing content possible
for the brands that depend on us," said Ryo Chiba, Chief Technology
Officer of TINT. "Using Amazon Comprehend, we were able to significantly
increase the quality and accuracy of our platform's content analytics
capabilities, which identifies the right content for the most impactful
marketing campaigns. Amazon Comprehend allows us to focus on our core
product and not worry about the heavy lifting associated with building
our own machine learning models."
FamilySearch is the largest genealogical organization in the world and
is dedicated to connecting families across generations with the belief
that learning about our ancestors helps us better understand who we are.
"FamilySearch developed ‘Compare-a-face' using Amazon Rekognition to
help site users see which of their ancestors they most resemble based on
family photographs," said Tom Creighton, Chief Technology Officer and
Lead Architect at FamilySearch. "Amazon Rekognition was used to provide
an engaging experience that helped people relate to their forbearers in
a new way. We look forward to using Amazon Rekognition in the future for
other potential face matching experiences."
Limbik is the first Data Studio for short-form video. By annotating and
analyzing the contextual, visual and audible characteristics of video at
scale, and associating each attribute with actual viewing behavior,
Limbik uncovers the precise triggers of attention. Using artificial
intelligence, Limbik has developed a set of technology-enabled processes
to predict what content will be successful, with the attributes that
perform and the analytics explaining why. "Amazon Rekognition is a key
aspect of Limbik Annotate, our video analysis stack that leverages
machine learning and human analysis to identify key attributes of
short-form video content," said Zach Schwitzky, Chief Executive Officer
and Co-Founder of Limbik. "Having evaluated multiple third-party video
annotation services, Amazon Rekognition is the most precise, efficient
and seamless to integrate as part of a broader video analysis process."
VidMob is a technology platform that connects marketers with a global
network of expert editors, animators, and motion graphic designers.
"Amazon Comprehend and Amazon Transcribe services allow VidMob to build
high-quality machine learning text analysis into our Agile Creative
Suite, enabling us to help brand clients understand content performance
in ways never before possible," said Alex Collmer, Founder and Chief
Executive Officer of VidMob. "We are able to transcribe text from video
content, and quickly analyze it using Comprehend, allowing us to surface
actionable insights to both our creator community and our clients,
giving them a strategic edge in the market."
Enetpulse is a leading provider of sports data solutions to some of the
biggest brands in gaming and media across the globe. The company offers
sports data products, including sports data feeds or API services, and
sports data solutions, such as live scores and results data. "We offer
data related to 30-plus types of sports to more than 150 media companies
around the world," said Mads Møllegaard, Chief Technology Officer,
Enetpulse. "We translate over one million objects that pertain to a wide
array of sports. While we have professional translators in house, doing
manual translation is time consuming and not scalable. Amazon Translate
provides us with high-quality machine translation that requires little
post editing. This helps increase our professional translator
efficiency, thereby reducing costs and turnaround times."