This document provides an introduction to Amazon's artificial intelligence services, including Amazon Polly for text-to-speech, Amazon Rekognition for image and video analysis, and Amazon Lex for conversational interactions. It discusses how these services are powered by deep learning and machine learning techniques and are built to be high quality, easy to use, and cost effective.

1. © 2017, Amazon Web Services, Inc. or its Affiliates. All rights reserved.
Roland Keijzer - CTO Bynder
Dinah Barrett – AWS Solutions Architect
An Introduction to Amazon AI
Services
June 28, 2017

2. Artificial Intelligence
At Amazon

3. Running AI In Production on AWS Today

4. 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

5. The Advent Of
Deep Learning
Algorithms
Data
GPUs
& Acceleration
Programming
models
AWS

6. Amazon AI
Intelligent Services Powered By Deep Learning

7. AWS AI Suite

8. Introducing Amazon AI
Polly
Text-to-Speech
Rekognition
Image Analysis
Lex
ASR & NLU
Apache MXNet
Apache
Deep learning framework
aws.amazon.com/amazon-ai

9. Apache MXNet
Programmable Portable High Performance
Near linear scaling
across hundreds of GPUs
Highly efficient
models for mobile
and IoT
Simple syntax,
multiple languages

10. Why Apache MXNet?
Most Open Best On AWS
Optimized for
deep learning on AWS
Accepted into the
Apache Incubator
(Integration with AWS)

11. One-Click
Deep Learning
AWS Deep Learning AMIs
Amazon Linux & Ubuntu
Up to~40k CUDA cores
Apache MXNet
TensorFlow
Theano
Keras
Caffe
CNTK
Torch
Pre-configured CUDA drivers
Anaconda, Python3
Out-of-the-box Tutorials
+ CloudFormation template
+ Container Image
Available in the AWS Marketplace

12. Introducing Amazon AI
Polly
Text-to-Speech
Apache MXNet Rekognition
Image Analysis
Lex
ASR & NLU
Apache
Deep learning framework
aws.amazon.com/amazon-ai

13. Amazon Polly: Life-like Speech Service
Converts text
to life-like speech
47 voices 24 languages Low latency,
real time
Fully managed

14. “Today in London it’s 25 °C”
1. Automatic, Accurate Text Processing
Polly: A Focus On Voice Quality & Pronunciation

15. Polly: A Focus On Voice Quality & Pronunciation
2. Intelligible and Easy to Understand
1. Automatic, Accurate Text Processing
She sells sea shells by the sea shore. The
shells she sells are surely seashells. So if
she sells shells on the seashore, I'm sure
she sells seashore shells

16. 2. Intelligible and Easy to Understand
3. Add Semantic Meaning to Text
“Dinah’s number is "07867123123”
“Dinah’s number is "07867123123”
Telephone Number
Polly: A Focus On Voice Quality & Pronunciation
1. Automatic, Accurate Text Processing

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

18. Amazon Polly: Life-like Speech Service
High quality,
through
best-in-class
deep learning
Deep
functionality
Easy to use
& thoughtfully integrated
Built for
production
Low
Cost
(free tier)
Upload your own text through the console and start using Amazon Polly today!
https://aws.amazon.com/polly

19. Introducing Amazon AI
Polly
Text-to-Speech
Apache MXNet Rekognition Lex
Image Analysis ASR & NLU
Apache
Deep learning framework
aws.amazon.com/amazon-ai

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

21. 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

22. Rekognition: Facial Detection
Emotion: calm: 73%
Sunglasses: false (value: 0)
Mouth open wide: 0% (value: 0)
Eye closed: open (value: 0)
Age: 28.57 (value: 28.57)
Glasses: no glass (value: 0)
Mustache: false (value: 0)
Beard: no (value: 0)

23. Demographic Data
Facial Landmarks
Sentiment Expressed
Image Quality
Facial Analysis
Brightness: 25.84
Sharpness: 160
General Attributes
Rekognition: Facial Analysis

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

25. High quality,
through
best-in-class
deep learning
Deep
functionality
Easy to use
& thoughtfully integrated
Built for
production
Low
Cost
(free tier)
Rekognition: Search & Understand Visual Content
https://aws.amazon.com/rekognition

26. Introducing Amazon AI
Polly
Text-to-Speech
Apache MXNet Rekognition Lex
Image Analysis ASR & NLU
Apache
Deep learning framework
aws.amazon.com/amazon-ai

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

28. Lex: Build Natural, Conversational Interactions In Voice & Text
Voice & Text
“Chatbots”
Powers
Alexa
Voice interactions
on mobile, web
& devices
Text interaction
with Slack, FB Messenger
and Twilio
Enterprise
Connectors
Salesforce
Microsoft Dynamics
Marketo
Zendesk
Quickbooks
Hubspot

29. High quality,
through
best-in-class
deep learning
Deep
functionality
Easy to use
& thoughtfully integrated
Built for
production
Low
Cost
(free tier)
Lex: Build Natural, Conversational Interactions In Voice & Text
https://aws.amazon.com/lex
Build your bot with Amazon Lex!

30. Amazon Lex - Technology
Amazon Lex
Automatic Speech
Recognition (ASR)
Same technology that powers Alexa
Cognito CloudTrail CloudWatch
AWS Services
Action
AWS Lambda
Authentication
& Visibility
Speech
API
Language
API
Fulfillment
End-Users
Developers
Console
SDK
Intents,
Slots,
Prompts,
Utterances
Input:
Speech
or Text
Multi-Platform Clients:
Mobile, IoT, Web,
Chat
API
Response:
Speech (via Polly TTS)
or Text
Natural Language
Understanding (NLU)

31. Amazon AI: What’s Next?
Polly
Text-to-Speech
Apache MXNet
Deep learning framework
Rekognition Lex
Image Analysis ASR & NLU
New APIs
and tools
Apache

36. 1984
15 GB/mo
1994
29 TB/mo
2004
1.3 EB/mo
2014
42 EB/mo

51. References
• AWS AI Blog
• Getting Started with Amazon Polly
• Getting Started with Amazon Lex
• Getting Started with Amazon Rekognition
• Getting Started with Deep Learning

52. Thank you!