Building intelligent applications using AI services

1. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.S U M M I T
Build Intelligent Applications Using AI Services
Prakash Palanisamy
Solutions Architect
Amazon Web Services
A I M 0 0 1

2. S U M M I T © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.
Put machine learning in the
hands of every developer
Our mission at AWS

3. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.S U M M I T
Our Approach for Machine Learning
Customer-focused
90%+ of our ML roadmap is
defined by customers
Multi-framework
Support for the most
popular frameworks
Pace of innovation
200+ new ML launches and major
feature updates in the
last year
Breadth and depth
A wide range of AI and ML services in-
production
Security and analytics
Deep set of security and
encryption features, with robust
analytics capabilities
Embedded R&D
Customer-centric approach to
advancing the state of the art

4. Some of our machine learning customers…

5. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.S U M M I T
AI Services
R E K O G N I T I O N
I M A G E
P O L L Y T R A N S C R I B E T R A N S L A T E C O M P R E H E N D L E XR E K O G N I T I O N
V I D E O
F O R E C A S TT E X T R A C T P E R S O N A L I Z E
VISION SPEECH LANGUAGE CHATBOTS FORECASTING RECOMMENDATIONS
ML Services Amazon
SageMaker Ground Truth Notebooks Algorithms + Marketplace
Reinforcement
Learning Training Optimization Deployment Hosting
ML Frameworks +
Infrastructure EC2 P3
& P3dn
EC2
C5 FPGAs Greengrass
Elastic
inference
FRAMEWORKS INTERFACES INFRASTRUCTURE
Inferentia
EC2
G4

6. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.S U M M I T
AI Services
Pre-trained AI services that require
no ML skills or training
Easily add intelligence to your
existing apps and workflows
Quality and accuracy from
continuously-learning APIs
A I S E R V I C E S
R E O G N I T I O N
I M A G E
P O L L Y T R A N S C R I B E T R A N S L A T E C O M P R E H E N D
& C O P R E H E N D
M E D I C A L
L E XR E K O G N I T I O N
V I D E O
Vision Speech Chatbots
F O R E C A S TT E X T R A C T P E R S O N A L I Z E
Language Forecasting Recommendations

7. S U M M I T © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.
Real-time personalization and recommendation service,
based on the same technology used at Amazon.com.
No ML experience required.

8. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.S U M M I T
Users increasingly expect every interaction to be personalized
Activity & Product
Recommendation
Search
Personalization
Personalized
Notifications
Emails

9. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.S U M M I T
Personalization offers material business results
Engagement
(up to 15% increase)
Product
Discovery
(up to 80% clicks on tail
items)
Revenue
(up to 5% increase)
Conversion
(up to 30% increase)

10. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.S U M M I T
Effective personalization involves multiple hard problems
Popularity Trap
Naïve models give recommendations similar to popular items
Cold Starts
New users should get relevant recommendations, new items should show in recommendations
Scale
Recommendations should scale across millions of users and items
Real-Time
Personalization must be responsive to the changing user intent
Custom models
Personalization models must accurately reflect business context and user behavior

11. Amazon Personalize: machine learning personalization and
recommendations
Articles, products,
videos, etc.
Age, location, etc. Amazon
Personalize
Customized
personalization &
recommendation
API
Views, signups,
conversion, etc.

12. Amazon Personalize: machine learning personalization and
recommendations
Customized
personalization &
recommendation
API
F u l l y m a n a g e d b y A m a z o n
P e r s o n a l i z e
Amazon Personalize
INSPECT
DATA
IDENTIFY
FEATURES
SELECT
ALGORITHMS
SELECT
HYPERPARAMETERS
TRAIN
MODELS
OPTIMIZE
MODELS
HOST
MODELS
BUILD FEATURE
STORE
CREATE
REAL-TIME
CACHES
Activity stream
from app
Inventory
Demographics
(optional)
DeepFM | FFNN | HRNN | Popularity-Count | Personalized Ranking | SIMS

13. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.S U M M I T
Predictor Metrics
Metric Name Explanation Example
Normalized discounted
cumulative gains @ K
Considers positional effects by applying inverse
logarithmic weights based on the positions of
relevant items, normalized by ideal
recommendations.
!
"#$ !%&
'
!
"#$ !%(
'
!
"#$ !%)
!
"#$ !%!
'
!
"#$ !%&
'
!
"#$ !%(
= 0,71
Precision @ K Total relevant items divided by total recommended
items.
*
+
= 0,6
Mean reciprocal ranks @ K Considers positional effects by computing the mean
of the inverse positions of all relevant items.
,-./(
1
2
+
1
*
+
1
+
) = 0,344
for each of these, higher numbers are better

14. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.S U M M I T
Improve customer experiences with personalization and
recommendations
Real-time Works with almost any
product or content
K E Y F E A T U R E S
Responsive to changes
in intent
Automated
machine learning
Bring existing algorithms
from Amazon SageMaker
Deliver high quality
recommendations
Deep learning
algorithms
Easy to Use

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16. S U M M I T © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.
Accurate time-series forecasting service, based
on the same technology used at Amazon.com.
No ML experience required.

17. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.S U M M I T
The perils of
poor predictions
in forecasting…
Time
Forecast
Sales
Sales
Forecasting too low results in opportunity cost, disappointed customers.
Forecasting too high results in higher costs for customers and excess
inventory.

18. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.S U M M I T
Traditional methods struggle with generating accurate forecasts
Can’t handle
seasonality
Don’t consider related
variables such as price,
holiday and promotions,
that impact forecast
accuracy
Can’t handle new
items, that don’t
have historical
time-series data

19. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.S U M M I T
Amazon Forecast
Accurate time series forecasting service, based on the same
technology used at Amazon.com. No machine learning experience
required.
• Draws from 20 years of experience in forecasting at Amazon
• Packages a suite of 8 algorithms that includes 5 deep-learning
algorithms and 3 statistical methods. The deep-learning
algorithms improve accuracy by up to 50%, for datasets with
over 1000 time-series.
ARIMA | DeepAR+ | ETS | MDN | MQRNN | NPTS | Prophet | SQF

20. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.S U M M I T
Historical data
Supply chain,
inventory, etc.
Customized
forecasting API
Related “causal” data
Weather, special offers, product
details
Amazon Forecast
Amazon Forecast: Machine learning time-series forecasting

21. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.S U M M I T
Historical data
Supply chain,
inventory, etc.
Customized
forecasting API
Inspect
data
Identify
features
Select
from 8
algorithms
Select
hyperparameters
Host
models
Load
data
Train
models
Optimize
models
Related “causal” data
Weather, special offers, product
details
F u l l y m a n a g e d b y A m a z o n
F o r e c a s t
Amazon Forecast
Amazon Forecast: Machine learning time-series forecasting

22. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.S U M M I T
Predictor Metrics
Root Mean Square Error (RMSE):
• Measures the difference between the values predicted by the model and the actual values in the
test dataset.
1
"
#
$%&
'
()*+", − ./0)1+23 4
Prediction Quantiles:
• Quantile loss (QL) calculates how far off the forecast is from actual demand in either direction
as a percentage of demand on average in each quantile.
56 7 =
2 . ∑ 7. max ()*+", − ./0)1+23, 0 + 1 − 7 . max ./0)1+23 − ()*+",, 0
∑ ()*+",

23. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.S U M M I T
Amazon Forecast: Machine learning time-series forecasting
Any historical
time-series
Export to CSV to
Integrate with SAP and
Oracle Supply Chain
Custom forecasts
with 3 clicks
Up to 50% more
accurate
1/10th
the cost
Retail demand Travel demand AWS usage
Revenue forecasts Web traffic Advertising demand
Generate
forecasts for:

24. S U M M I T © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.

25. S U M M I T © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.
OCR++ service to easily extract text and data from
virtually any document. No ML experience required.

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How documents are processed today
Optical Character
Recognition (OCR)
Manual
processing
Rules and
template-based extraction

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Amazon Textract Features
Text extraction Table extraction Form extraction
• No code or templates to maintain
• Lower document processing costs (only $1.50/1,000 documents)

28. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.S U M M I T
Amazon Textract - Text Extraction
Blocks: PAGE, PARAGRAPH, LINE, WORD
is washed by waves, and cooled

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Amazon Textract - Table Extraction
Blocks: PAGE, TABLE, CELL
For each ’block’ you get:
• Text
• Confidence score
• Block relationships (e.g. cells within a table)

30. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.S U M M I T
Amazon Textract - Form extraction
Blocks: PAGE, KEY_VALUE_SET
For each ’block’ of your document:
• Form field name (key) and field value (value) association
• Confidence score
• Page number
• Block relationships

31. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.S U M M I T
Supports single-page
documents such
as images (e.g.,
mobile capture)
For multi-page documents,
up to 3,000 pages
Amazon Textract
Sync and Async

32. S U M M I T © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.

33. S U M M I T © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.
Easily add intelligent image and video analysis to your
applications.

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Amazon Rekognition:
Deep Learning-Based Image and Video Analysis

35. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.S U M M I T
Amazon Rekognition Benefits
Low cost
Your data
is your ownServerless
Rapid
integration
State of the
art capabilities
Continuous
improvement

36. S U M M I T © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.
Discover insights and relationships in text

37. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.S U M M I T
Amazon Comprehend
Di s c o v e r i n s i g h t s a n d r e l a t i o n s h i p s i n t e x t
Entities
Key Phrases
Language
Sentiment
Syntax
Grouping

38. S U M M I T © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.
Accurately extract health information from patient
notes, clinical trial reports, and other electronic
health records using Amazon Comprehend

39. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.S U M M I T
Amazon Comprehend Medical
Entities
Medication
Medical condition
Test, treatments, and
procedures anatomy
Protected Health
Information (PHI)
Relationship extraction
Medication
Test, treatments, and procedures
Entity traits
Negation
Diagnosis signs and symptom

40. S U M M I T © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.

41. S U M M I T © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.
Turn text into lifelike speech using deep learning

42. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.S U M M I T
Amazon Polly – Use Cases
Contact
Centers
Special Needs
AI Assistant
Voiced videos
and presentations
Language
learning
Amazon Polly
Navigation
Podcasting,
Voiced blogs
and news articles

43. S U M M I T © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.
Conversational interfaces for your applications
powered by the same deep learning technologies as
Alexa

44. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.S U M M I T
Amazon Lex – use cases
CONTACT CENTER BOTS
Customer service IVR
Account inquiries
Bill payments
Service updates
Single Sign On
Users / Roles
Groups
Auditing / Monitoring
Risk & Compliancy
Insights
SECURITY
INFORMATIONAL BOTS
Answer questions
News updates
Weather information
Game scores
APPLICATION BOTS
Conversational interfaces
Book tickets
Order food
Manage bank accounts
Single Sign On
Users / Roles
Groups
Auditing / Monitoring
Risk & Compliancy
Insights
SECURITY
PRODUCTIVITY BOTS
Enterprise efficiencies
Check sales numbers
Inventory status
Expense reports
IoT BOTS
Device interactions
Kiosks
Appliances
Auto
A service for building conversational interfaces into your applications using voice and text

45. S U M M I T © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.
Natural and accurate language translation

46. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.S U M M I T
21 Languages
417 Combinations
Key Features
Real-time
< 500ms / sentence on average
< 150ms / conversational / short form
Tag Handling
XML tags placement maintains
styling and formatting through
translation
< / >
Data Security
Data ownership
Encryption
Access Management
Ease of Use
Simple API calls and partner
solutions
$15/1M characters
Or $0.000075 per word;
Pay as you go, 2M characters
monthly free tier
HIPAA Eligible

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Automatic speech recognition

48. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.S U M M I T
Amazon Transcribe – Key Features
Channel
Identification
Custom
vocabulary
Speaker
Identification
Word-level
time stamps
Punctuation and
capitalization
Word-level
confidence scores

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Live Streaming with Automated Multi-Language Subtitling
Refer: https://github.com/awslabs/live-streaming-with-automated-multi-language-subtitling

51. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.S U M M I T
Document extraction for NLP
Quickly turn extracted text/data into actionable insights
Input
Uploaded document
images of medical
notes, explanation of
benefits, and
patient forms
Amazon S3
Uploaded documents
are stored in S3
Amazon
Comprehend
Use natural language
processing to extract
insights from
medical documents
Amazon
Elastisearch Service
Easily search through
extracted data and
text insights
Output
Discover medical
insights to improve
patient care
Amazon Textract
Automatically extract
words and lines of
text, and tables

52. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.S U M M I T
Translator Chatbot
Amazon
S3 Website
AWS
Lambda
Amazon
DynamoDB
Amazon
Lex
Amazon
Polly
Amazon
Translate
Amazon
Cognito
Translation
bot
Synthesize
speech
Get
Translation
Cached
Translation
Refer: https://aws.amazon.com/blogs/machine-learning/create-a-translator-chatbot-using-
amazon-translate-and-amazon-lex/

53. S U M M I T © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.

54. Thank you!
S U M M I T © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.
Prakash Palanisamy
pprakash

55. S U M M I T © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.