amazon 인공 지능(ai) 서비스 및 aws 기반 딥러닝 활용 방법 - 윤석찬 (aws,...
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© 2016, Amazon Web Services, Inc. or its Affiliates. All rights reserved.
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•https://www.youtube.com/watch?v=gQpMDdJmbNs
© Jeff Dean, Trends and Developments in Deep Learning Researchhttp://www.slideshare.net/AIFrontiers/jeff-dean-trends-and-developments-in-deep-learning-research
Accuracy
Scale (data size, model size)
1980s and1990s
neural networks
other approaches
© Jeff Dean, Trends and Developments in Deep Learning Researchhttp://www.slideshare.net/AIFrontiers/jeff-dean-trends-and-developments-in-deep-learning-research
more computeAccuracy
Scale (data size, model size)
neural networks
other approaches
1980s and1990s
© Jeff Dean, Trends and Developments in Deep Learning Researchhttp://www.slideshare.net/AIFrontiers/jeff-dean-trends-and-developments-in-deep-learning-research
more computeAccuracy
Scale (data size, model size)
neural networks
other approaches
Now
© Jeff Dean, Trends and Developments in Deep Learning Researchhttp://www.slideshare.net/AIFrontiers/jeff-dean-trends-and-developments-in-deep-learning-research
2016
3% errors
2011
5% errors
humans
26% errors© Jeff Dean, Trends and Developments in Deep Learning Research
http://www.slideshare.net/AIFrontiers/jeff-dean-trends-and-developments-in-deep-learning-research
http://techneedle.com/archives/29063
"아마존 상품 배송 선반에는 물건이뒤죽박죽 보관되고 있다. 예를 들면영화 DVD, 로션, 피클이 한 칸에 보관되어 있다. 자투리 공간 없이 창고공간을 100% 활용할 수 있고, ‘이상품군은 어디에 보관해야 한다’ 등배워야 할 내용이 줄어든다. 게다가실수로 잘못 꺼내는 일도 적다. 상품보관을 위한 기술은 컴퓨터 비전과실내 위치 추적 등의 시스템을 활용한다"
Original image Activation map Binary map
2.0
1.0
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https://www.amazon.com/b?node=16008589011
The image part with relationship ID rId7 was not found in the file.
The image part with relationship ID rId7 was not found in the file.
Amazon Echo sales up 9X compared to last year, company says in holiday roundup of 2016 winter sold “millions” of Echo devices.
https://www.wired.com/2017/01/ces-alexa-in-everything
Create Great Content:
ASK is how you connectto your consumer
Supported by two powerful frameworks
A L E X AV O I C ES E R V I C E
UnparalleledDistribution:
AVS allows your contentto be everywhere
Lives In The Cloud
Automated SpeechRecognition (ASR)
Natural Language Understanding (NLU)
Always Learning
A L E X AS K I L L SK I T
Alexa Skills Kit 구조도
Amazon Alexa
Service
Developer’s Application
Service
Amazon’s Developer
Portal애플리케이션, 사용자의도,샘플데이터, 개발자서비스등정보전달
사용자의도를서비스로전달
GUI 카드를알렉사앱에전달
오디오를서비스로전송오디오결과를렌더링해서재생
텍스트결과및GUI 카드정보전달
Alexa Skill 만들기 – AWS Lambda 기반 VoiceOps
https://www.youtube.com/watch?v=azKYe4IWTxA
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https://github.com/alexa/alexa-avs-sample-app/wiki/Raspberry-Pi
16 years = 140,160 hours≈14,016 hours of speech
고객 기술지원
영업 지원
고객지원
프로페셔널 컨설팅
교육 및인증
보안 및 빌링시스템
파트너생태계
솔루션아키텍트
엔터프라이즈
가상 테스크톱
기업용 공유도구
기업용 이메일
백업 및 복구
글로벌 리전 (Region) 가용 영역 (AZ) 콘텐츠 배포 지점(Edges)
인프라
기본 서비스컴퓨팅VMs, Auto-scaling, Load Balancing, Containers, Cloud functions
스토리지Object, Blocks, File, Archival, Import/Export
데이터베이스Relational, NoSQL, Caching, Migration
네트워킹VPC, DX, DNS
콘텐츠 배포 (CDN)
하이브리드환경
데이터백업
통합 앱 개발 환경
전용 회선연결
통합 인증
통합 리소스관리
네트워크통합
서비스접근 제어
사용자인증 관리
암호 키 관리 및 저장
모니터링로그
기업 자원설정 및 보고
리소스 사용량 및 감사
보안 및 규정 준수
기업 내규정 준수 웹 방화벽
비지니스애플리케이션
비지니스인텔리전스 데이터베이스DevOps
도구네트워킹보안 스토리지
IoT
규칙 엔진
디바이스쉐도우
디바이스SDK
디바이스레지스트리
디바이스게이트웨이
개발 및 운영 도구모바일 서비스앱 서비스데이터 분석
데이터웨어하우스
Hadoop/Spark
실시간 데이터저장
머신 러닝
Elastic Search 서비스
알람 및 큐서비스
워크 플로우
풀텍스트검색
Email 전송
동영상 변환
원 클릭 앱 개발
모바일 인증
기기 동기화
모바일 앱테스트
푸시 알림
DevOps 리소스관리
앱 라이프사이클관리 도구
콘테이너 서비스
클라우드 함수
리소스 템플릿
API Gateway
실시간 데이터분석
비지니스 인텔리전스
모바일 분석
모바일 허브
마켓 플레이스
Amazon Machine Learning
P2 InstanceDeep Learning
AMI and templateInvestment in
MXNet
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vCPU 32 / RAM 488GB GPU 8 x NVIDIA K80
p2.8xlarge= $7.2 per hour
x 20vCPU 640 GPU 160
p2.8xlarge x 20= $144 per hour
$aws ec2-run-instances ami-b232d0db--instance-count 20--instance-type p2.8xlarge--region us-east-1
$aws ec2-stop-instances i-10a64379 i-10a64280 ...
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http://bit.ly/deepami
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https://github.com/awslabs/ecs-deep-learning-workshop
•ü https://github.com/dmlc/mxnet/tree/master/dockerü https://hub.docker.com/r/kaixhin/cuda-mxnet/
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https://www.slideshare.net/AIFrontiers/scaling-deep-learning-with-mxnet
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1 2 3
- 데이터 소스로 부터DataSource 생성
- 데이터 내용과스키마 확인
- 모델링 진행
- 생성된 모델의품질 확인
- 모델에 해석상세 조절
--
컴퓨터비전 API
온라인부정지불감시
클라우드소싱기반지도서비스
자율주행컴퓨터비전분석
대용량기계학습 부동산구매예측분석 동영상추천엔진개발 고객트래픽분석
스포츠플레이예측 이미지인식기반검색
Zestimate 서비스(Apache Spark 활용)
보험리스크분석
Amazon Machine Learning 기반 모델 훈련 및 예측
https://youtu.be/4loLsXKlJUM
Flower
ChairCoffee Table
Living Room
Indoors
Maple
Villa
Plant
Garden
Water
Swimming Pool
Tree
Potted Plant
Backyard
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Female
Happy
Smiling
Male
No Facial Hair
Happy
Female
Sad
No Eyeglasses
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f7a3a278-2a59-5102-a549-a12ab1a8cae8 &v1
02e56305-1579-5b39-ba57-9afb0fd8782d&v2
Face ID & vector<float>Face
4c55926e-69b3-5c80-8c9b-78ea01d30690&v3
tran
sfor
med
stor
ed
{f7a3a278-2a59-5102-a549-a12ab1a8cae8, 02e56305-1579-5b39-ba57-9afb0fd8782d,4c55926e-69b3-5c80-8c9b-78ea01d30690}
IndexFace Collection
Amazon Rekognition 살펴 보기
https://youtu.be/yrldn0JciIU
Training
Conv 1 Conv 2 Conv n
…
…
Feature Maps
Fully Connected
Layer
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Amazon Polly
“The temperature in WA is 75°F”
“The temperature in Washington is 75 degrees Fahrenheit”
"We live for the music", live from the Madison Square Garden.
"We live(리브) for the music", live(라이브) from the Madison SquareGarden.
<speak>
My name is Kuklinski. It is spelled
<prosody rate='x-slow'><say-as interpret-as="characters">Kuklinski</say-as>
</prosody>
</speak>
My daughter’s name is Kaja.<lexeme>
<grapheme>Kaja</grapheme><grapheme>KAJA</grapheme><phoneme>"kaI.@</phoneme>
</lexeme>
Amazon Polly 살펴 보기
https://youtu.be/yrldn0JciIU
RSS Feed Amazon Polly
Amazon CloudWatch
Amazon S3AWS Lambda
1. Trigger
2. Check
3. Content
4. Text 5.Audio
6.Audio
https://github.com/awslabs/amazon-polly-sample
Amazon RekognitionAWS SDK
for iOS
Amazon Cognito Amazon Polly
Amazon S3 Bucket
Skate, Car, Street, Parking, Town
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FacebookMessengerMobile
Book Hotel
“Book a Hotel inNYC”
Hotel Booking
New York City
Natural Language Understanding
Intent/Slot Model
UtterancesHotel BookingCity New York City
CheckIn Nov 30th
CheckOut Dec 2nd
“Your hotel is booked for Nov 30th”
Polly Confirmation: “Your hotel is booked for Nov 30th”
The image part with relationship ID rId3 was not found in the file.“Can I go ahead
with the booking?
a
in NYC
Automatic Speech Recognition
Amazon Lex
Automatic Speech Recognition (ASR)
Natural Language Understanding (NLU)
Same technology that powersAlexa
Cognito CloudTrail CloudWatch
AWS Services
Action AWSLambda
Authentication &Visibility
SpeechAPI
Language API
Fulfillment
End-Users
Developers
Console
SDK
Intents, Slots, Prompts, Utterances
Input: Speech or Text
Multi-Platform Clients: Mobile, IoT, Web,
Chat
API
Output:Speech (via PollyTTS) or Text
BookHotel
Amazon Lex를 통한 호텔 예약 챗봇 만들기
https://youtu.be/c1YC8mIiWh0
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Amazon Rekognition
AWS SDKfor iOS
Amazon CognitoAmazon Polly
AWSLambda
Amazon S3 Bucket
Amazon SNS
Amazon Lex
Amazon S3 Bucket
à
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AmazonRekognition
AmazonLex
AWS IoT
AWSLambda
Amazon S3
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P2Amazon
Machine Learning Deep LearningAMI and template
Investment inMXNet
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