Speaker: Osemeke Isibor, Solutions Architect, AWS AWS offers a family of intelligent services that provide cloud-native machine learning and deep learning technologies to address your different use cases and needs. For developers looking to add managed AI services to their applications, AWS brings natural language understanding (NLU) and text-to-speech (TTS) with Amazon Polly, visual search and image recognition with Amazon Rekognition, and developer-focused machine learning with Amazon Machine Learning. In this talk you will learn about these services and see demos of their capabilities

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Osemeke Isibor,
Solutions Architect.
iosemeke@amazon.com
31st October 2017
Artificial Intelligence and Machine
Learning Services on AWS

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Agenda
• Introduction
• Amazon AI
• Amazon Machine Learning
• Conclusion

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Artificial Intelligence At Amazon
Thousands Of Employees Across The Company Focused on AI
Discovery &
Search
Fulfilment &
Logistics
Enhance
Existing Products
Define New
Categories Of
Products
Bring Machine
Learning To All

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AI on AWS Today
•Zillow
–Zestimate (using Apache Spark)
•Howard Hughes Corp
–Lead scoring for luxury real estate purchase predictions
•FINRA
–Anomaly detection, sequence matching, regression
analysis, network/tribe analysis
•Netflix
–Recommendation engine
•Pinterest
–Image recognition search
• DataXu
–Leverage automated & unattended ML at
large scale (Amazon EMR + Spark)
• Mapillary
–Computer vision for crowd sourced maps
• Upserve
–Restaurant table mgmt & POS for
forecasting customer traffic
• TuSimple
–Computer Vision for Autonomous Driving
• Clarifai
– Computer Vision APIs

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We Help Customers
Put Intelligence At The Heart Of
Every Application & Business

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AI Services
AI Platform
AI Engines
Amazon
Rekognition
Amazon
Polly
Amazon
Lex
Apache
MXNet
TensorFlow Caffe Theano KerasTorch CNTK
Amazon AI: Democratized Artificial Intelligence
Amazon
Machine Learning
EMR & Spark

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Amazon AI
Intelligent Services Powered By Deep Learning

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Amazon AI: Deep Learning Services
RekognitionLex
Life-like Speech Image AnalysisConversational Engine
Polly

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Amazon Lex
Conversational Engine

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The Advent Of Conversational Interactions
1st Gen: Machine-oriented
interactions

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The Advent Of Conversational Interactions
1st Gen: Machine-oriented
interactions
2nd Gen: Control-oriented
& translated

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The Advent Of Conversational Interactions
1st Gen: Machine-oriented
interactions
2nd Gen: Control-oriented
& translated
3rd Gen:
Intent-oriented

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Lex: Build Natural, Conversational
Interactions in Voice & Text
Voice & Text
“Chatbots”
Powers
Alexa
Voice interactions
on mobile, web
& devices
Text interaction
with Slack & Messenger
Enterprise
Connectors
(with more coming) Salesforce
Microsoft Dynamics
Marketo
Zendesk
Quickbooks
Hubspot

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Lex Use Case: Informational Bots

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Lex Use Case: Application Bots

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Some Lex Customers

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Amazon Polly
Life-like Speech

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Polly: Life-like Speech Service
Converts text
to life-like speech
47 voices 27 languages
and voices
Low latency,
real time
Fully managed

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Let’s Hear from Polly..

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“Today in Seattle, WA, it’s 11°F”
‘"We live for the music" live from the Madison Square Garden.’
1. Automatic, Accurate Text Processing
Polly: A Focus On Voice Quality & Pronunciation

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Polly: A Focus On Voice Quality & Pronunciation
2. Intelligible and Easy to Understand
1. Automatic, Accurate Text Processing

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2. Intelligible and Easy to Understand
3. Add Semantic Meaning to Text
“Richard’s number is 2122341237“
“Richard’s number is 2122341237“
Telephone Number
Polly: A Focus On Voice Quality & Pronunciation
1. Automatic, Accurate Text Processing

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2. Intelligible and Easy to Understand
3. Add Semantic Meaning to Text
4. Customized Pronunciation
“My daughter’s name is Kaja.”
“My daughter’s name is Kaja.”
Polly: A Focus On Voice Quality & Pronunciation
1. Automatic, Accurate Text Processing

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Polly Use Case: Content Creation

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Polly Use Case: Customer Contact Centre

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Some Polly Customers

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Amazon Rekognition
Image Analysis

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Rekognition: Search & Understand Visual Content
Real-time &
batch image
analysis
Object & Scene
Detection
Facial Detection Face SearchFacial Analysis

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Rekognition: Object & Scene Detection
Bay
Beach
Coast
Outdoors
Sea
Water
Palm_tree
Plant
Tree
Summer
Landscape
Nature
Hotel
99.18%
99.18%
99.18%
99.18%
99.18%
99.18%
99.21%
99.21%
99.21%
58.3%
51.84%
51.84%
51.24%
Category Confidence

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Rekognition: Facial Detection

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Rekognition: Facial Analysis
Emotion: calm: 73%
Sunglasses: false (value: 0)
Gender: female (value: 0)
Mouth open wide: 0% (value: 0)
Eye closed: open (value: 0)
Glasses: no glass (value: 0)
Mustache: false (value: 0)
Beard: no (value: 0)

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Rekognition: Compare Faces

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Rekognition: Facial Search
Facial
verification
Face
Search
Visual Similarity
Search
(compare two faces) (compare many faces) (find similar faces)

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Rekognition: Celebrity Rekogniton

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Rekognition: Image Moderation

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Rekognition Use Case: Image Moderation

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Rekognition Use Case: Sentiment Analysis

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Some Rekognition Customers

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Amazon Machine Learning

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Powerful machine learning technology
Powerful ML technology Pay-as-you-go pricing
Integrates with AWS services Fully managed service
Quick and easy to start

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How It Works :Training your Model
HISTORICAL DATA
XXXXXXXXXXXXXX +
Amazon ML
=෍
𝑘=0
𝑛
𝑛
𝑘
𝑥 𝑘
MODEL

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How it Works: Recommendation/ Prediction
NEW DATA
XXXXXXXX + =MODEL
Predictions /
Recommendations
Amazon ML

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And a few more use case examples…
Fraud detection Detecting fraudulent transactions, filtering spam emails,
flagging suspicious reviews, …
Personalization Recommending content, predictive content loading,
improving user experience, …
Targeted marketing Matching customers and offers, choosing marketing
campaigns, cross-selling and up-selling, …
Content classification Categorizing documents, matching hiring managers and
resumes, …
Churn prediction Finding customers who are likely to stop using the
service, upgrade targeting, …
Customer support Predictive routing of customer emails, social media
listening, …

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Some Amazon Machine Learning Customers

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DIY Machine Learning

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Conclusion: Get Started
https://aws.amazon.com/amazon-ai/what-is-ai/

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Osemeke Isibor,
Solutions Architect
iosemeke@amazon.com