An Overview of AI at AWS

1. An Overview of AI at AWS
Prakash Palanisamy, Solutions Architect | 11th Oct, 2018
© 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved.

2. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved.
Amazon.com,1995

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« Two Decades of Recommender Systems at Amazon.com » (2017)
https://www.computer.org/csdl/mags/ic/2017/03/mic2017030012.html
G.D. Linden, J.A. Jacobi, and E.A. Benson,
Collaborative Recommendations Using
Item-to-Item Similarity Mappings, US
Patent 6,266,649, to Amazon.com, Patent
and Trademark Office, 2001 (filed 1998).

4. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved.
Our deep experience with AI/ML differentiates our approach
Product
recommendation
engine
Robot-enabled
fulfillment
centers
New
product
categories
Amazon has invested in AI/ML since our
inception, and we share our knowledge and
capabilities with our customers
20181995
Natural language
processing-supported
contact centers
ML-driven supply
chain and
capacity planning
Checkout-free
shopping
using deep learning

5. ML @ AWS: Our Mission
Put Machine Learning in the hands of every developer and data scientist

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Application
Services
Platform
Services
Frameworks
&
Infrastructure
API-driven services: Vision & Language Services, Conversational Chatbots
Deploy machine learning models with high-performance machine learning
algorithms, broad framework support, and one-click training, tuning, and
inference.
Develop sophisticated models with any framework, create managed, auto-
scaling clusters of GPUs for large scale training, or run inference on trained
models.
AWS ML Stack

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The Amazon Machine Learning Stack
PLATFORM SERVICES
APPLICATION SERVICES
FRAMEWORKS & INTERFACES
Caffe2 CNTK
Apache
MXNet
PyTorch TensorFlow Chainer Keras Gluon
AWS Deep Learning AMIs
Amazon SageMaker
Rekognition Transcribe Translate Polly Comprehend Lex
AWS
DeepLens
EDUCATION
Amazon EMR

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Customer Running ML on AWS Today

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Application
Services API-driven services: Vision & Language Services, Conversational Chatbots
AWS ML Stack

10. Amazon Rekognition
Deep learning-based visual analysis service

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Amazon
Rekognition
Object and scene
detection
Facial analysis
Face comparison
Celebrity recognition
Image moderation
Deep learning-based visual analysis service

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Object & Scene Detection

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Facial Analysis

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Crowd-Mode Face Detection

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Facial Search

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Explicit Nudity
Nudity
Graphic Male Nudity
Graphic Female Nudity
Sexual Activity
Partial Nudity
Suggestive
Female Swimwear or Underwear
Male Swimwear or Underwear
Revealing Clothes
Image Moderation

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Celebrity Recognition

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Text in Image

19. http://www.marinusanalytics.com/articles/2017/10/17/amazon-rekognition-helps-marinus-analytics-fight-human-trafficking
Amazon Rekognition Helps Marinus
Analytics Fight Human Trafficking

20. Amazon Rekognition Video
Deep learning-based visual analysis service

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Video in. People, activities, and details out.
Objects, scenes, and activities
Person detection and recognition
Celebrity recognition
Inappropriate content detection
Amazon Rekognition Video

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24. Amazon Lex
Conversational Interfaces

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Intents
A particular goal that the
user wants to achieve
Utterances
Spoken or typed phrases
that invoke your intent
Slots
Data the user must provide to fulfill the
intent
Prompts
Questions that ask the user to input
data
Fulfillment
The business logic required to fulfill the
user’s intent
BookHotel

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Lex Bots
Salesforce
Microsoft Dynamics
Marketo
Zendesk
Web
Devices
Apps
Facebook Messenger,
Slack,
Amazon
Connect
Mobile
Mobile Hub
integration
Quickbooks
Amazon Lex: Conversational Chatbots

27. Amazon Translate
Neural Machine Translation Service

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Real-time
translation
Powered by Deep
Learning
26 Language pairs Language detection
Amazon Translate
Natural and fluent language translation

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Translate API example
aws translate translate-text
--endpoint-url https://translate.us-east-1.amazonaws.com
--region us-east-1
--text "hello, what’s up? Do you want to go see a movie tonight?"
--source-language-code "en"
--target-language-code "fr”
{
"TargetLanguageCode": "fr”,
"TranslatedText": "Bonjour, quoi de neuf ? Tu veux aller voir un film ce soir ?”,
"SourceLanguageCode": "en”
}

30. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved.
Translate API example
aws translate translate-text
--endpoint-url https://translate.us-east-1.amazonaws.com
--region us-east-1
--text "hello, what’s up? Do you want to go see a movie tonight?"
--source-language-code "en"
--target-language-code "fr”
{
"TargetLanguageCode": "fr”,
"TranslatedText": "Bonjour, quoi de neuf ? Tu veux aller voir un film ce soir ?”,
"SourceLanguageCode": "en”
}
Context Awareness

31. Amazon Polly
Deep learning-based Text-to-Speech service

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Amazon Polly
Deep Learning-based text-to-speech service
Amazon Polly
“Hoi! mijn naam
is Lotte. Ik lees
elke tekst voor
die je hier
invoert.”

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<speak xml:lang="en-US">
De prijs van dit boek is <prosody rate="60%"> €45</prosody>
</speak>
A Focus On Voice Quality & Pronunciation
Support for Speech Synthesis Markup Language (SSML) Version 1.0
https://www.w3.org/TR/speech-synthesis

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Polly API example
aws polly synthesize-speech
--text "It was nice to live such a wonderful live show"
--output-format mp3
--voice-id Joanna
--text-type text johanna.mp3
aws polly synthesize-speech
--text-type ssml
--text file://ssml_polly
--output-format mp3
--voice-id Joanna speech.mp3

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“With Amazon Polly our users benefit from
the most lifelike Text-to-Speech voices
available on the market.”
Severin Hacker
CTO, Duolingo

36. Amazon Transcribe
Automatic speech recognition service

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Amazon Transcribe
Automatic speech recognition service
“Hello, this is Allan
speaking”
Amazon
Transcribe

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Amazon Transcribe
Automatic speech recognition service
Support for
telephony
audio
Timestamp
generation
Intelligent
punctuation
and formatting
Recognize
multiple
speakers
Custom
vocabulary
Multiple
languages

39. Amazon Comprehend
Natural Language Processing

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Amazon Comprehend
Natural Language Processing
Discover valuable insights from text
Entities
Key Phrases
Language
Sentiment
Amazon
Comprehend

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Amazon Comprehend - Topic modeling
STORM
WORLD SERIES
AUSTRALIA
STOCK
MARKET
WASHINGTON
HEALTH
CRISIS
MACHINE
LEARNING
LIBRARY OF
NEWS ARTICLES *
Amazon
Comprehend

42. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved.
Comprehend API example
aws comprehend detect-sentiment
--text "I love you"
--language-code "en”
{
"SentimentScore":
{
"Mixed": 0.005664939060807228,
"Positive": 0.9262985587120056,
"Neutral": 0.06511948257684708,
"Negative": 0.0029170133639127016
},
"Sentiment": "POSITIVE”
}

43. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved.
Platform
Services
AWS ML Stack
Deploy machine learning models with high-performance machine learning
algorithms, broad framework support, and one-click training, tuning, and
inference.

44. Amazon EMR
Easily Run and Scale Apache Hadoop, Spark, HBase,
Presto, Hive, and other
Big Data Frameworks

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ML Applications on Amazon EMR
Amazon EMR
(Elastic MapReduce)

46. Amazon SageMaker
A fully managed service to quickly and easily build
machine-learning based models

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End-to-End
Machine Learning
Platform
Zero setup Flexible Model
Training
Pay by the second
$
Amazon SageMaker
Build, train, and deploy machine learning models at scale

48. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved.
Frameworks
&
Infrastructure
AWS ML Stack
Develop sophisticated models with any framework, create managed, auto-
scaling clusters of GPUs for large scale training, or run inference on trained
models.

49. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved.
Amazon EC2 P3 Instances
• Up to eight NVIDIA Tesla V100 GPUs
• 1 PetaFLOPs of computational
performance – 14x better than P2
• 300 GB/s GPU-to-GPU communication
(NVLink) – 9X better than P2
• 16GB GPU memory with 900 GB/sec peak
GPU memory bandwidth
T h e f a s t e s t , m o s t p o w e r f u l G P U i n s t a n c e s i n t h e c l o u d

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AWS Deep Learning AMI
• Easy-to-launch tutorials
• Hassle-free setup and configuration
• Pay only for what you use
• Accelerate your model training and deployment
• Support for popular deep learning frameworks

51. AWS DeepLens
Deep learning enabled video camera for developers

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A new way to learn
Custom built for deep learning
Broad Framework Support
Deploy models from Amazon SageMaker
Integrated with AWS
Full programmable with AWS Lambda
AWS DeepLens
W o r l d ’ s f i r s t d e e p l e a r n i n g e n a b l e d v i d e o c a m e r a f o r d e v e l o p e r s

53. AWS Greengrass
Machine learning inference locally on Greengrass Core

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AWS Greengrass Core
A Software to run subset of AWS IoT Core in local compute
environment

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ML Inference using AWS Greengrass
Train in the cloud
• Massive computing power
• Large repository of data
Trained models
and Lambdas
Extracted
IntelligenceInferences and
take actions
locally on device
AWS Cloud
for training
Inference at the edge
• Low latency
• bandwidth saving
• regulation/privacy

56. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved.
https://aws.amazon.com/answers/media-entertainment/media-analysis-solution/
https://github.com/aws-samples/aws-ai-qna-bot
DEMO

57. Thank you!!!