Transformção digital usando machine_learning

© 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.
Drive digital transformation
usingAI

© 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.S U M M I T
Centerpiece for digital transformation
Customer
experience
Business
operations
Decision
making
Innovation Competitive
advantage
of digital transformation initiatives
supported by AI in 201940%

Our mission at AWS
Put machine learning in the hands
of every developer

Our unique approach
Customer-focused
90%+ of our ML roadmap
is defined by customers
Breadth & depth
More AI and ML services
in production than any
other provider
Embedded R&D
Customer-centric approach to
advancing the state of the art
Security & analytics
Deepest set of security and
encryption features, with robust
analytics capabilities
Multi-framework
Support for the most popular
frameworks
Pace of innovation
200+ new ML launches
in the last year

customers have used
machine learning on AWS
10,000+
AWS holds the top spots on Stanford’s
deep learning benchmark, DAWN, for
fastest training time, lowest cost, lowest
inference latency
of TensorFlow projects in the cloud
run on AWS85%
of deep learning in the cloud runs on
AWS81%

More machine learning happens on AWS than anywhere else

Culture
Technology

Bringing AI into your
digital transformation
requires a new “stack”
that makes it easier to
put ML to work
Technology

M L F R A M E W O R K S &
I N F R A S T R U C T U R E
The Amazon ML stack: Broadest & deepest set of capabilities
A I S E R V I C E S
Vision | Documents | Speech | Language | Chatbots | Forecasting | Recommendations
M L S E R V I C E S Data labeling | Pre-built algorithms & notebooks | One-click training and deployment
Build, train, and deploy machine learning models fast
Easily add intelligence to applications without machine
learning skills
Flexibility & choice, highest-performing infrastructure
Support for ML frameworks | Compute options purpose-built for ML

The Amazon ML stack: Broadest & deepest set of capabilities
A I S E R V I C E S
R E K O G N I T I O N
I M A G E
P O L L Y T R A N S C R I B E T R A N S L A T E C O M P R E H E N D
& C O M P R E H E N D
M E D I C A L
L E XR E K O G N I T I O N
V I D E O
Vision Speech Chatbots
A M A Z O N
S A G E M A K E R
B U I L D T R A I N
F O R E C A S TT E X T R A C T P E R S O N A L I Z E
D E P L O Y
Pre-built algorithms & notebooks
Data labeling (G R O U N D T R U T H )
One-click model training & tuning
Optimization (N E O )
One-click deployment & hosting
M L S E R V I C E S
F r a m e w o r k s I n t e r f a c e s I n f r a s t r u c t u r e
E C 2 P 3
& P 3 d n
E C 2 C 5 F P G A s G R E E N G R A S S E L A S T I C
I N F E R E N C E
Reinforcement learning
Algorithms & models ( A W S M A R K E T P L A C E
F O R M A C H I N E L E A R N I N G )
Language Forecasting Recommendations

Put AI to work for your business
Pre-trained AI services that require
no ML skills or training
Easily add intelligence to your existing
apps and workflows
Quality and accuracy from
continuously-learning APIs
A I S E R V I C E S
I M A G E
& C O M P R E H E N D
M E D I C A L
L E XR E K O G N I T I O N
V I D E O
Vision Speech Chatbots
F O R E C A S TT E X T R A C T P E R S O N A L I Z E
Language Forecasting Recommendations

Modernize your contact center to improve customer service
conversational chat bots | call transcription | intelligent routing | sentiment analysis | VoC analytics text-to
speech | multilingual omni-channel communication
P O L L Y T R A N S C R I B E T R A N S L A T E C O M P R E H E N D L E X

Meaningful
customer interactions
Vonage uses Amazon Lex and Amazon Polly
to develop natural language-driven conversational
apps to respond to customer requests with real-
time and contextual intelligence, improving
response time, and
quality of service.

Use AI services to strengthen safety & security
accurate facial analysis | identity protection | metadata extraction
C O M P R E H E N D &
C O M P R E H E N D M E D I C A L
I M A G E
V I D E O

Real-time
identity verification
Aella Credit uses Amazon Rekognition to
analyze images to verify an individual’s identity in
real-time without human intervention, allowing it to
provide instant loans to eligible customers through
its mobile app.

Identify Child-
Trafficking Victims
Faster
Thorn Uses Amazon Rekognition to Help Law
Enforcement Identify Child-Trafficking Victims
Faster

Automate media workflows to reduce costs & monetize content
content moderation | contextual ad insertion | searchable media library
custom facial recognition | multi-language metadata search
C O M P R E H E N DR E K O G N I T I O N
I M A G E
V I D E O
T R A N S C R I B E T R A N S L A T E T E X T R A C T

Scaling video indexing
C-SPAN uses Amazon Rekognition to
automatically index video news footage
for search. With Rekognition, C-SPAN
reduced indexing time per video from 1
hour to 20 minutes and uploaded 97,000
images in under 2 hours.

Reduce localization costs & improve accuracy
custom vocabulary | timestamp generation | secure real-time translation | language identification

Scaling
real-time translation
Using Amazon Translate, Lionbridge is able to
scale machine translation in order to localize
content faster and in more languages. Using
Translate, Lionbridge was able to reduce translation
costs by 20 percent.

Targeted
customer acquisition
VidMob uses Amazon Rekognition and
Amazon Transcribe for metadata extraction
and sentiment analysis, to help marketers
understand which videos resonate with audiences.
This allows marketers to promote targeted content
to acquire new customers.

Personalize customer experiences with targeted recommendations
recommendation technology used by Amazon.com | context-aware recommendations sentiment
analysis | VoC analytics
P E R S O N A L I Z E C O M P R E H E N DR E K O G N I T I O N
I M A G E
V I D E O
NEW

Personalizing
customer experiences
Domino’s uses Amazon Personalize to customize
and scale relevant marketing communications to
customers based on time, context, and content,
thereby improving and enhancing their experience
with the Domino’s brand.

Accurately forecast future business outcomes
forecasting technology used by Amazon.com | multiple time-series data
forecast scheduling & visualization | supply chain integration
F O R E C A S T
NEW

Increase efficiency with automated document analysis
optical character recognition (OCR) | automatic data extraction | natural language processing
intelligent search | text analytics
C O M P R E H E N D &
C O M P R E H E N D M E D I C A L
T E X T R A C T
NEW

ML was too complicated for everyday developers
Collect and
prepare
training data
Choose and
optimize your
ML algorithm
1
2
3
Train and
tune model
(trial and error)
Set up and
manage
environments
for training
Deploy model
in production
Scale and manage
the production
environment

Custom machine learning for your business
Amazon SageMaker
Fast & accurate
data labeling
Built-in, high
performance
algorithms &
notebooks
B U IL D
1
One-click
training and
tuning
TR AIN
Model optimization
2
Fully managed
hosting with
auto-scaling and
elastic inference
One-click
deployment
D EPL OY
3

Custom machine learning for your business
One-click
model training
& deployment
10x
better algorithm
performance
Train once
run anywhere
AMAZON SAGEMAKER
70%
cost reduction for data labeling
using Ground Truth
2x
performance increases from
model optimization with Neo
75%
cost reduction for inference
with Elastic Inference
R ED U C E C O STS IN C R EASE
PER F OR MAN C E
EASE - O F - U SE

Advancing pharma research
& discovery
Celgene uses Apache MXNet on Amazon
SageMaker for toxicology prediction to virtually
analyze biological impacts of potential drugs
without putting patients at risk. A model that once
took 2 months to train can now be trained in 4
hours.

Fueling product
innovation
Using Amazon SageMaker, Intuit developed ML
models that can pull a year’s worth of bank
transactions to find deductible business expenses for
customers. Using SageMaker, Intuit reduced
machine learning deployment time by 90%, from 6
months to 1 week.

Driving better
healthcare outcomes
Using Amazon SageMaker, GE Healthcare
developed an ML model that can learn from
thousands of medical scans to detect anomalies
more accurately and efficiently, allowing radiologists
to prioritize patients needing immediate attention.

Optimizing supply chain
operations
Using Amazon SageMaker, Convoy builds and
trains machine learning models to optimize
driver schedules and to ensure load balancing,
capacity planning, pricing and payments.

Increasing customer
engagement
Using Amazon SageMaker, Tinder analyzes millions
of match requests a minute, billions
of swipes a day, across more than 190 countries
to make the perfect match. With Amazon
Rekognition, Tinder creates tags to highlight
photos, resulting in 20% increase in engagement.

Accelerating
financial analysis
Using TensorFlow on Amazon SageMaker,
Siemens Financial Services developed an
NLP model to extract critical information to
accelerate investment due diligence, reducing time
to summarize diligence documents from 12 hours
down to 30 seconds.

Highest-performing infrastructure for your business
Fastest and lowest-cost
compute options for ML
workloads
Elastic compute to provision just-
right compute for your ML
workloads
Build custom algorithms using
the ML frameworks
F r a m e w o r k s I n t e r f a c e s I n f r a s t r u c t u r e
E C 2 P 3
& P 3 d n
E C 2 C 5 F P G A s G R E E N G R A S S E L A S T I C
I N F E R E N C E

The best place to run TensorFlow
Amazon SageMaker is the best
place to run TensorFlow in the
cloud
S T O C K T E N S O R F L O W
A W S - O P T I M I Z E D T E N S O R F L O W
• Fully-managed training and hosting
• Near-linear scaling across 100s of GPU
• 75% lower inference costs with Amazon
Elastic Inference
• 3x faster network throughput with EC2 P3
65%
90%
S c a l i n g e f f i c i e n c y w i t h 2 5 6 G P U s

Store & retrieve
your data
Comprehensive
analytics
Protect
your data
Delivers
99.999999999%
durability
Up to 400%
faster data
queries
Deepest set of security
&
encryption features
The broadest & deepest capabilities for machine learning

Culture
Setting your
organization up for
success

Assess your structured
and unstructured
data sources
Create
the loop
1.
Connect technology
initiatives with
business outcomes
Advance your
data strategy
Put machine learning
in the hands of
your developers
Organize
for success
2. 3.
?

• Build machine learning models in Amazon
SageMaker
• Train, test, and iterate on the track using the AWS
DeepRacer 3D racing simulator
• Compete in the world’s first global autonomous
racing league, to race for prizes and a chance to
advance to win the coveted AWS DeepRacer Cup
AWS DeepRacer
A fully autonomous 1/18th-scale race car designed to help you learn about reinforcement
learning through autonomous driving

• Purpose-built for ML-skills development
• Fully programmable & customizable
• Build custom Amazon SageMaker models
• 10-minutes to your first deep learning project
AWS DeepLens
The world’s first deep learning-enabled video camera for developers

ml.aws

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Transformção digital usando machine_learning

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