1. © 2018, Amazon Web Services, Inc. or its affiliates. All rights reserved.
Olivier Klein
Head of Emerging Technologies, Asia-Pacific
눈으로 보는 AWS 기반 인공지능 서비스
아키텍처 활용 데모
@captainklein

2. Self-Driving cars or
assisted driving
Voice assistants, IVR
and chatbots
Recommendation engines
Fraud detection
Incentives for reduced
customer churn
Computer assisted health diagnosis
Anomaly detection in
manufacturing
Demand forecasting in F&B
Spam E-Mail filtering
Facial recognition
airport check-in

3. HUMAN
CENTRIC

4. Natural Language
Understanding
Computer VisionVoice and ASR

5. Alexa, Hello!

6. Dial into meetings
Control In-Room Conferencing Systems
Set room temperature or lighting
Book meeting rooms
Replenish office supplies
Schedule meetings
and much more…
Use your voice to…

7. Assisted Interactions
Intelligent Voice Responses
Chatbots
Funneling of incoming requests …
Hi, how can I help you today?
I want to make a reservation for a
table tonight at 8 p.m.
Great, I can help you with that,
how many of you will come
tonight?
Requests
Intentions
Amazon Lex
Fulfill
automatically
Reroute to correct
funnel

8. Facial Recognition
Airport check-in
Loyalty recognition
Faster Immigration …
Amazon Rekognition

9. A m a z o n S u m e r i a n
The fastest and easiest way to create VR, AR, and 3D experiences

10. Display screen
Consumer
Amazon Lex
AWS Cloud
Mobile Phone /
Tablets
Amazon Sumerian
Amazon Lex listens to the voice, interprets the intent
and responds via an Amazon Sumerian host

11. How about augmented reality
experiences?

12. AR.js is fast. It can
run scenes at 60 fps
even on older
phones
FAST
Get your users
running your app as
soon as they can.
No install!
IMMEDIATE
Open source, JavaScript framework for
building web based Augmented Reality
applications.
Amazon Sumerian and AR.js
Browser Based
Augmented Reality

13. AWS IOT
connected through
ardemo.sumerian.world

14. ardemo.sumerian.world
AWS IOT
connected through

15. © 2018, Amazon Web Services, Inc. or its affiliates. All rights reserved.
Deep Learning and
Computer Vision

16. Learn independently with little
supervision
Simulates how our brains learn by
creating artificial "neural networks"
Especially useful in computer vision
– learn from the data with little to no
feature engineering
D e e p L e a r n i n g : D e e p N e u r a l N e t w o r k

17. Convolutional Neural Networks (CNNs)
Connectivity pattern between neurons
resembles the organization of the animal
visual cortex
Inspired by the receptive field of the animal
cortex it exploits local correlations in images
Finds applications in image recognition, facial
recognition, or video analysis

18. Retrain classificationFeature Extraction
Convolutional Neural Network
Amazon Sagemaker
In-Built algorithm for transfer learning

19. SSD – Single Shot MultiBox Detector
downsample
body
class predictor
box predictor
input scale 0 scale 1
class predictor
box predictor

20. Joseph Redmon
YOLO - You Only Look Once
Real-Time Object Detection
Darknet – Open source Neural Networks in C

21. EC2
NVIDIA
Tesla V100 GPUs
P3
Deep Learning AMI
Amazon S3
Darknet
Training Images
Model Output
Infer Model on
Camera
AWS Greengrass
AWS Cloud Edge Location

22. Labelling and annotating the dataset can be an intensive task
Tip: Record a video in multiple settings and lights and extract frames

23. Labelling and annotating the dataset can be an intensive task
Tip: Record a video in multiple settings and lights and extract frames

24. Building ground truth data is an
intensive task
Need human intelligence
to annotate data sets
Facebook AI Research
DigitalGlobe | Radiant
Amazon Mechanical Turk

25. How is object detection and
identification useful?

26. Object identification and
recognition
Real Time, Per Pixel
Object Segmentation
Centimeter-accurate
positioning

27. Model
Training
Inference
in the Cloud
Inference
at the Edge
Building Intelligent Systems in the Cloud and at the Edge

28. AWS Greengrass ML
Includes pre-built TensorFlow and Apache MXNet package
for all devices powered by Intel Atom, NVIDIA Jetson TX2,
and Raspberry Pi
Makes it easy to deploy your machine learning model from
the cloud to your devices
Infer locally reduces latency and cost to predict - Data is sent
only to the cloud only when it requires additional processing

29. Zhe Cao, Tomas Simon, Shih-
En Wei, Yaser Sheikh, Tomas
Simon, Hanbyul Joo, Iain
Matthews, Varun Ramakrishna,
Takeo Kanade
Carnegie Mellon
Perceptual Computing Lab

30. Serverless App
AWS Greengrass
Camera + Model Inference Consumer
Body & Hands
coordinates
AWS IOT
AWS Cloud

31. Fully programmable video camera
Optimized for deep-learning on the device with Apache
MXNet, Caffe, TensorFlow
Tutorials, sample code, examples and pre-built models
Integrated with Amazon Sagemaker for custom models
AWS DeepLens
A deep learning-enabled video camera for developers

32. Object and Scene
Detection
Facial
Analysis
Face
Recognition
Text in Image
Deep learning-based computer vision service for images and video
Unsafe Image
Detection
Celebrity
Recognition
A m a z o n R e k o g n i t i o n

33. Monitoring App
Camera (Edge Site) ConsumerAWS Cloud
DatalakeAmazon S3
Amazon Rekognition
Local Camera Compliance footage
(picture & video)
Real-time facial
detection

34. Monitoring App
Camera (Edge Site) ConsumerAWS Cloud
Datalake
Amazon S3
Amazon Rekognition
Local Camera
Local real-time
facial detection
AWS Greengrass
Only forward
relevant footage

35. ServerlessElastic capacityAggressive migration
At the Edge, On IoT DevicesPre-built imagesNew data created on AWS
PredictionTrainingData
GPUs and CPUsTons of GPUsPBs of existing data

36. © 2018, Amazon Web Services, Inc. or its affiliates. All rights reserved.
감사합니다!
Olivier Klein
Head of Emerging Technologies, Asia-Pacific
@captainklein

37. © 2018, Amazon Web Services, Inc. or Its Affiliates. All rights reserved.
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38. © 2018, Amazon Web Services, Inc. or its affiliates. All rights reserved.
감사합니다!
Olivier Klein
Head of Emerging Technologies, Asia-Pacific
@captainklein