The digital transformation evolution will rely on the benefits of computer vision and natural language processing to enable new business models to align the physical and digital world for citizens. In this session, learn how to deploy machine learning models to leverage the power of smart devices using Alexa, as well as process data quickly at the edge – even without connectivity – using smart cameras and autonomous agents.

1. P U B L I C S E C T O R
S U M M I T
O T T A W A

2. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.P U B L I C S E C T O R
S U M M I T
Machine Learning at the Edge
Alex Coqueiro
Public Sector Solutions Architecture Team
AWS
@alexbcbr #AWSPSSummit #AWS_GOV

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S U M M I T
Applying Machine Learning @ the edge

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S U M M I T

5. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.P U B L I C S E C T O R
S U M M I T
Caffe implementation of
image classification
Trained on EC2 P2 instances
but running on edge
(Fulfillment Center)

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S U M M I T
Some of our machine learning customers…

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S U M M I T

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S U M M I T

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S U M M I T
Voice/sound
recognition
Smart
Cities
Image
recognition
Anomaly
detection
More
!
Smart
Agriculture
Predictive
maintenance
Self-driving
cars
Video
surveillance
Robotics
Use Cases

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S U M M I T
How it works…

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S U M M I T
DATA

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S U M M I T
Let’s build a solution
https://commons.wikimedia.org/wiki/File:Lake_Agnes_im_Banff_National_Park.jpg#metadata

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S U M M I T
V O I C E R E P R E S E N T S T H E
N E X T M A J O R D I S R U P T I O N
I N C O M P U T I N G

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S U M M I T
A L E X A , W H A T I S T H E W E A T H E R I N O T T A W A ?
Speech
Platform
Weather
“Speak” directive
Intent
Recognition result
Intent
Recognition result
Text/SSML
W A K E W O R D
D E T E C T I O N
S P E E C H
C A P T U R E
T E X T T O
S P E E C H O U T P U T
A l e x a Vo i c e S e r v i c e
Alexa’s voice
Recognize
User’s utterance
Alexa’s voice
ASR
NLU
Skill
TTS
A L E X A , Q U E L L E E S T L A M É T É O À O T T A W A ?

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S U M M I T

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S U M M I T

17. © 2018, Amazon Web Services, Inc. or its affiliates. All rights reserved.
© 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.P U B L I C S E C T O R
S U M M I T
The Alexa Service
Alexa
Skills
Kit
Alexa
Voice
Services

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S U M M I T
Semi-supervised learning technique
https://developer.amazon.com/blogs/alexa/post/9e8392c6-5476-4a34-a2d8-c4e479677954/new-speech-recognition-experiments-
demonstrate-how-machine-learning-can-scale
Transfer Learning combined
with LSTM
(long-short-term-memory)
get a car to <Destination>
get me a car
…

19. Infrastructure management
Your "skill" code

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S U M M I T
GetTicketIntent
Intent
Utterances and Intents
Alexa, ask National Park the cost of the ticket
wake word utteranceskill namelaunch

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S U M M I T
A W S L A M B D A
AWS Lambda lets you run code without provisioning or managing
servers.

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S U M M I T
COMPUTER VISION enables machines to
capture and analyze visual data on its own,
then make decisions about it.

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S U M M I T

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S U M M I T
Inferences and
local actions on
device
Extracted
intelligence
Trained model
Deploying inference locally

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S U M M I T
AWS Deep Learning AMI
Amazon Elastic
Compute Cloud
(Amazon EC2) c5 p3
Amazon SageMaker
Experimenting and training in the cloud

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S U M M I T
Convolution layer
When combined across multiple layers, convolution is able to
learn hierarchical features, with increasing levels of abstraction
Layer 1 – Edges Layer 2 – Curves
Layer N –
Classes

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S U M M I T
Building a neural network for image classification
from mxnet.gluon import nn
net = nn.Sequential()
net.add(nn.Conv2D(channels=6, kernel_size=5, activation='relu'),
nn.MaxPool2D(pool_size=2, strides=2),
nn.Conv2D(channels=16, kernel_size=3, activation='relu'),
nn.MaxPool2D(pool_size=2, strides=2),
nn.Flatten(),
nn.Dense(120, activation="relu"),
nn.Dense(84, activation="relu"),
nn.Dense(10))

28. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.P U B L I C S E C T O R
S U M M I T
A new way to learn
Custom built for Deep Learning
Broad framework support
Deploy models from Amazon SageMaker
Integrated with AWS
Fully programmable with AWS Lambda
AWS DeepLens
HD video camera
Custom-designed
Deep Learning
engine
Micro-SD
Mini-HDMI
USB
USB
Reset
Audio out
Power

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S U M M I T
AWS DeepLens

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S U M M I T
Using your own models with AWS DeepLens
• AWS DeepLens can run TensorFlow, Caffe, and Apache MXNet models
• Inception
• MobileNet
• NasNet
• ResNet
• And others
• Train or fine-tune your model
on Amazon SageMaker

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S U M M I T
… extend the concept for other use cases …
Medical equipment Industrial machinery Extreme environments

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S U M M I T
AWS Greengrass extends AWS onto your devices, so they
can act locally on the data they generate, while still taking
advantage of the cloud.
Data processed
in the cloud
Data processed
locally
Moving to the edge
AWS Greengrass

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S U M M I T
Inferences and
local actions on
device
Extracted
intelligence
Trained model
and Lambda function
Deploying and predicting with AWS Greengrass

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S U M M I T
Amazon SageMaker Neo: Train once, run anywhere
Neo

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S U M M I T
Exploring Business Domains in Movement

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S U M M I T
Empowering of autonomous agents
EPISODESTATE

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S U M M I T
Reinforcement Learning in the real world
Reward positive
behavior
DO NOT reward
negative
behavior
The result!

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S U M M I T
• 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

39. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.P U B L I C S E C T O R
S U M M I T
Under the hood
• 1:18 4WD scale car
• Intel Atom Processor
• System Memory: 4 GB RAM
• System Storage: 32 GB (expandable)
• 802.11ac Wi-Fi
• 4 MP Camera (MJPEG)
• Ubuntu 16.04.3 LTS
• ROS Kinetic
• Intel OpenVINO toolkit
• Car Battery: 7.4V/1100mAh Lithium
Polymer Battery
• Computer Battery: 13600 mAh USB-C PD
• 4x USB-A, 1x USB-C, 1x Micro-USB, 1x
HDMI

40. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.P U B L I C S E C T O R
S U M M I T
AWS Cloud
AWS
DeepRacer
NAT gateway
VPC
AWS DeepRacer
Models
Simulation
video
Metrics
AWS DeepRacer simulator architecture

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S U M M I T
AWS RoboMaker
A service that makes it easy for
developers to develop, test, and
deploy robotics applications, as
well as build intelligent robotics
functions using cloud services

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S U M M I T
We are not spectators, but actors
of the future
Herb Simon, 2000

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S U M M I T
ml.aws
@alexbcbr
#AWSPSSummit #AWS_GOV

44. Thank you!
© 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.P U B L I C S E C T O R
S U M M I T
Alex Coqueiro
Public Sector Solutions Architecture Team
AWS