The document provides an overview of artificial intelligence capabilities on AWS, including Amazon Polly for text-to-speech, Amazon Rekognition for computer vision, Apache MXNet as a deep learning framework, and Amazon Lex for building conversational bots. It describes their features and common use cases, such as using computer vision for facial analysis and recognition, building conversational interfaces for devices with Amazon Lex, and more.

1. © 2015, Amazon Web Services, Inc. or its Affiliates. All rights reserved.
Grant McCarthy
Enterprise Solutions Architect
August 17th, 2017
An Overview of AI on AWS

2. Artificial Intelligence
at Amazon

3. Artificial Intelligence
At Amazon

4. An Overview of AI on AWS
Apache
Amazon
Polly
Text-to-Speech
Amazon
Rekognition
Amazon
Lex
Computer Vision ASR & NLU
Apache
MXNet
Deep learning framework

5. An Overview of AI on AWS
Apache
MXNet
Apache
Deep learning framework

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

7. Apache MXNet is the deep learning framework
of choice for AWS

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

9. P2 INSTANCES DL CLOUD FORMATION
TEMPLATE
DL AMIS

10. An Overview of AI on AWS
Amazon
Polly
Text-to-Speech
Apache

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

12. Let’s take a listen…

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

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

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

16. 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.”
1. Automatic, Accurate Text Processing
Amazon Polly:
A Focus On Voice Quality & Pronunciation

17. Amazon Polly: Common Use Cases
• Internet of Things (smart home, connected devices)
• Education (language learning, training videos)
• Voiced Media (news, blogs, email)
• Voiced Chat Bots (Amazon Lex, Alexa skills)
• Gaming (avatars, Amazon Lumberyard)

18. An Overview of AI on AWS
Amazon
Rekognition
Computer Vision
Apache

19. Amazon Rekognition: Computer Vision Service
Object and Scene
Detection
Facial
Analysis
Facial
Comparison
Facial
Recognition

20. Amazon Rekognition: Object & Scene Detection

21. Amazon Rekognition: Computer Vision Service
State-of-the-art face recognition (bounding box and key features).

22. Face Attribute Extraction (emotion, gender, race, age, etc.)
Emotion: confused: 4%, 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: (value: 0)
Amazon Rekognition: Computer Vision Service
demo

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

24. Amazon Rekognition: A few use cases
Best photo: use the attributes smile and eyesOpen to determine the best photos to post
Demographic detection: collect the age and gender of customers in your store
Sentiment capture: detect the emotions of your customers as they try your product
A/B tuning: identify visually similar alternatives to high-scoring images for A/B testing
Smart filtering: identify images with high visual similarity to ensure only one is displayed
Verify face: compare two faces, receive a confidence score that they are the same person
Protected images: identify visually similar images that are protected by trademarks

25. An Overview of AI on AWS
Amazon
Lex
ASR & NLU
Apache

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

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

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

29. Amazon Lex .. for Conversational Interactions
Powered by the same deep learning technology as Alexa
Enterprise SaaS Connectors
Deployment to chat platforms, like Slack, FB
Messenger, Twilio SMS
Build Voice and Text Chatbots
Interactions on mobile, web, and devices

30. Informational Bot: Example

32. Amazon Lex Use Cases
Informational Bots
Chatbots for everyday consumer requests
Application Bots
Build powerful interfaces to mobile applications
• News updates
• Weather information
• Game scores ….
• Book tickets
• Order food
• Manage bank accounts ….
Enterprise Productivity Bots
Streamline enterprise work activities and improve efficiencies
• Check sales numbers
• Marketing performance
• Inventory status ….
Internet of Things (IoT) Bots
Enable conversational interfaces for device interactions
• Wearables
• Appliances
• Auto ….

33. AI Solutions for Every Developer

34. https://aws.amazon.com/amazon-ai/
Amazon AI: Getting Started

35. Thank you!
aws.amazon.com/amazon-ai

36. Q & A

37. Don’t Forget Evaluations !!