Mais conteúdo relacionado Semelhante a Build intelligent applications using AI services (20) Mais de Amazon Web Services (20) Build intelligent applications using AI services2. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.S U M M I T
Build intelligent applications using AI
Shafreen Sayyed
Senior Solutions Architect
Amazon Web Services
3. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.S U M M I T
• AWS AI Services
- Vision services
- Speech services
- Language services
- Forecasting
- Recommendations
• Customer Story: HSBC
4. 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
5. © 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
6. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.S U M M I T
The picture can't be displayed.
Some of our machine learning customers
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ML FRAMEWORKS &
INFRASTRUCTURE
The Amazon ML stack: Broadest & Deepest set of
capabilities
AI SERVICES
Vision | Documents | Speech | Language | Chatbots | Forecasting |
Recommendations
ML SERVICES
Data labeling | Pre-built algorithms & notebooks | One-click training and
deployment
Build, train, and deploy machine learning models fast
Easily add intelligence to applications without
machine learning skills
Flexibility & choice, highest-performing infrastructure
Support for ML frameworks | Compute options purpose-built for ML
8. © 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 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
& C O M 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
9. S U M M I T © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.
Deep learning-based image and video analysis service
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Amazon Rekognition Image
Facial Analysis Face Recognition
Text in ImageUnsafe Image Detection
Object & Scene Detection
Celebrity Recognition
11. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.S U M M I T
Amazon Rekognition Video
Object & Activity Detection Face Detection &
Recognition
Real-time Live StreamUnsafe Video DetectionCelebrity Recognition
Pathing
12. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.S U M M I T
Fighting Human Trafficking & Rescuing Victims
Uses Amazon Rekognition to power their Traffic Jam
FaceSearch tool
• “Using AI technology, like Amazon Rekognition, the
critical task of comparing images can now be done
with more accuracy and within seconds, compared to
days, which is so important in cases where detectives
have limited time to find the victim before he or she
is moved to the next city.”
- Emily Kennedy, President & Co-Founder, Marinus Analytics
13. 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.
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Amazon Textract - Key Benefits
Extract data quickly
and accurately
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Amazon Textract – Key Features
Text and Table
extraction
Bounding Boxes Form extraction
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Extract for NLP - Reference architecture
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
NLP
Use natural
language processing
to extract insights
from
medical documents
Amazon
Elasticsearch
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
17. S U M M I T © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.
Automatic speech recognition
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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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AWS Lambda
Amazon S3
Amazon
Athena
Audio Input
Amazon
QuickSight
Amazon
Comprehend
Amazon Transcribe − Integration
20. S U M M I T © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.
Natural and accurate language translation
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25 Languages
595 Combinations
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;
PAYG, 2M characters monthly free tier
HIPAA Eligible
Amazon Translate – Key Features
22. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.S U M M I T
High-Volume and Time-Sensitive Content
Share of worldwide digital content
• Legal Documents
• Healthcare Documents
• Advertising Materials
Machine Translation
• User-authored content
(Customer Service, Customer
Reviews, Forum Posts, Search)
• Text Analytics
(sentiment, Document
Classification, and more)
• Real-time Communication
• Content Discovery
Post-edited
Machine
Translation
23. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.S U M M I T
«We operate 90 localized websites in 41
languages. (…)
Having evaluated Amazon Translate
and several other solutions, we believe
that Amazon Translate presents a quick,
efficient and most importantly, accurate
solution. »
Matt Fryer, VP and Chief Data Science Officer, Hotels.com
24. 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
25. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.S U M M I T
Amazon Lex Bots - Key concepts
Utterances
Spoken or typed phrases that invoke
your intent
BookHotel
Intents
An intent performs an action in
response to natural language user input
Slots
Slots are input data required to fulfill
the intent
Fulfillment
Fulfillment mechanism for your intent
26. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.S U M M I T
Utterances
I want to book a hotel in
London
Can you help me book my
hotel?
I want to make my hotel
reservations
I’d like to book a hotel
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Slots
Slot Type Values
Destination City London, New York, Scotland
Check in Date Valid dates
Check out Date Valid dates
28. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.S U M M I T
“Book a hotel”
Book hotel
LON
“Book a hotel in
London”
Automatic speech
recognition
Hotel booking
London
Natural language
understanding
Intent/slot
Model
UtterancesHotel Booking
City London
Check in May 30th
Check out June 2nd
“Your hotel is booked for
May 30th”
Confirmation: “Your hotel is
booked for May 30th”
“Can I go ahead
with the booking?
a
in
Amazon Polly
29. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.S U M M I T
Amazon Lex
End to End
Speech to Intent
ASR+NLU
integrated into
one API
Dialog Management
Native support &
maintains context
Text to Speech
Amazon Polly integrated
into API
Business Logic
Native integration with
AWS Lambda
Deployment
One click deployment
Security
Encrypted data in
transit & at rest
Scale
Completely managed
service
Analytics
Monitor and improve
End to End
30. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.S U M M I T
© 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved.
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 ….
Contact Center Bots
Chatbots for customer service IVR
• Account inquiries
• Bill payment
• Service update ….
31. 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
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Amazon Polly - Key features
• 58 voices across 28 languages
• Wide selection of Voices and Languages
• Lip-syncing and text highlighting
• Fine-grained voice control
• Custom lexicons
• Optimize Streaming Audio
• Available in 18 AWS Regions
33. © 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 presentationsLanguage
learning
Amazon Polly
Navigation
Podcasting,
Voiced blogs
and news articles
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Amazon Polly
“Hi, my name is
Shafreen…”
Text-to-speech (TTS)
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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
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Managed contact center service in the cloud.
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Amazon Connect – Key Benefits
Real time and
historical analytics
High-quality
voice capability
Call recording
Skills-based routing
[Automatic Call Distribution (ACD)]
38. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.S U M M I T
NATURAL
Amazon Lex Chatbots use the
same technology that powers Alexa
DYNAMIC
Answer customer questions
before they are even asked
PERSONAL
Contact flows adapt on
a per customer basis
Ok, you are now
booked for a
9:00AM departure
tomorrow out of
London City,
arriving in
Glasgow at
11:45AM.
Flight
Booking
System
CRM
content
Hi Adam Hunt,
I see your flight
was cancelled
today. How can
I help you?
Contact flow engine – customer experience example
Incoming
customer
call Can you
please
rebook me
for the
same flight
tomorrow?
Great
Thank you!
39. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.S U M M I T
Workforce
ManagementAgent Data
Your Data
Warehouse
Metrics
Call
Recordings
Open platform/easy integrations
Contact
Flows
CRM
AWS
Lambda
Customer
Databases
Business
Intelligence
Contact
Control Panel
Your
S3 Storage
40. S U M M I T © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.
Discover insights and relationships in text
41. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.S U M M I T
Amazon Comprehend
Sentiment
Entities Language
Key phrases
Topic
modeling
Syntax
42. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.S U M M I T
Amazon Comprehend – Natural Language
Processing
Amazon.com, Inc. is located in
Seattle, WA and was founded July 5,
1994 by Jeff Bezos. Our customers
love buying everything from books to
blenders at great prices
Named Entities
Amazon.com: Organization
Seattle, WA : Location
July 5th,1994: Date
Jeff Bezos : Person
Keyphrases
Our customers
books
blenders
great prices
Sentiment
Positive
Language
English
43. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.S U M M I T
Sentiment Analysis
$ aws comprehend detect-sentiment
--language-code 'en' --text 'I love cloud!’
{
"Sentiment": "POSITIVE”,
"SentimentScore": {
"Mixed": 0.012617903761565685,
"Positive": 0.9599817991256714,
"Neutral": 0.021758323535323143,
"Negative": 0.005641999188810587
}
}
44. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.S U M M I T
AWS Text Analytics Workload
Amazon Kinesis
Amazon ES
Amazon Redshift
Amazon EMR
• Semantic
• Rich filtering
• Grouping, trends
• Joining, correlating
• Clustering
• Graph, search
• Near real-time
• Alerts
Amazon S3
Social media, support
Amazon Aurora
Articles, documents
45. © 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
46. S U M M I T © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.
Real-time personalization and recommendation service
47. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.S U M M I T
Amazon Personalize – Key Features
Real-time
Works with almost any
product or content
Responsive to changes
in intent
Automated
machine learning
Bring existing algorithms
from Amazon SageMaker
Deliver high quality
recommendations
Deep learning
algorithms
Easy to Use
48. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.S U M M I T
Customer Account
ITEMS
Articles, products,
videos, etc.
Amazon
Personalize
Training
USERS
Age, location, etc.
INTERACTIONS
Views, signups,
conversion, etc.
Amazon Personalize
Customized
personalization &
recommendation
API
Amazon Know-How
-- Algorithms
-- Hyperparameters
49. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.S U M M I T
Amazon
Personalize
Training
Amazon Personalize – Learning Pipeline
Customized
personalization &
recommendation
APIIDENTIFY
FEATURES
INSPECT
DATA
SELECT
HYPERPARAMTERS
SELECT
ALGORITHMS
OPTIMIZE
MODELS
TRAIN
MODELS
BUILD FEATURE
STORE
HOST
MODELS
CREATE
REALTIME
CACHES
50. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.S U M M I T
Amazon
Personalize
Training
Amazon Personalize – Learning Pipeline
Customized
personalization &
recommendation
APIIDENTIFY
FEATURES
INSPECT
DATA
SELECT
HYPERPARAMTERS
SELECT
ALGORITHMS
OPTIMIZE
MODELS
TRAIN
MODELS
BUILD FEATURE
STORE
HOST
MODELS
CREATE
REALTIME
CACHES
OVERRIDE
OVERRIDE
Custom Container in
EC2 Container Registry
51. S U M M I T © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.
Accurate time-series forecasting service
52. © 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:
53. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.S U M M I T
Customer Account
ITEM IDs
Products, Parts, EC2
Instance Types,
Workforce Type
Amazon
Forecast
Training
TIMESTAMP
Timestamps
relative the items
you want to
forecast
Customized
Forecasting
API
Amazon Know-How
-- Algorithms
-- Hyperparameters
DEMAND
Point in time demand
info for Products, EC2
instances
1…
3…
2…
10…
Amazon Forecast
54. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.S U M M I T
Amazon
Forecast
Training
Amazon Forecast - Learning Pipeline
IDENTIFY
FEATURES
INSPECT
DATA
SELECT
HYPERPARAMTERS
SELECT
ALGORITHMS
OPTIMIZE
MODELS
TRAIN
MODELS
BUILD FEATURE
STORE
HOST
MODELS
CREATE
REALTIME
CACHES
Customized
Forecasting
API
55. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.S U M M I T
Amazon
Personalize
Training
Amazon Forecast – Learning Pipeline
IDENTIFY
FEATURES
INSPECT
DATA
SELECT
HYPERPARAMTERS
SELECT
ALGORITHMS
OPTIMIZE
MODELS
TRAIN
MODELS
BUILD FEATURE
STORE
HOST
MODELS
CREATE
REALTIME
CACHES
OVERRIDE
OVERRIDE
Custom Container in
EC2 Container Registry
Customized
Forecasting
API
56. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.S U M M I T
Building a Virtual Assistant for Policy Advice at
HSBC
Gareth Butler
Senior Programme Manager
HSBC
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HSBC - The Worlds
Leading International
Bank
$53.8bn
235,00039
58. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.S U M M I T
Business challenges
Global Employee Demand for Information
• 235,000 staff in 67 locations
• Operating in many regulated markets
Use of internal resource searches and/or SME advisory services
• Employees self-serve via Intranet liaise with subject matter experts to find
information
• Multiple similar requests from several different internal sources
Query volumes
• High volume of query traffic given the scale of global operations
Opportunity identified or provision of information faster, easier, on demand
leveraging AWS Cloud technology …
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60. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.S U M M I T
61. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.S U M M I T
Solution Overview: Ingesting Policy Documents
User Interface Machine LearningProcessingStorage
HSBC User
Web UI
Web UI
Amazon S3
Amazon DynamoDB
Amazon Elasticsearch
Service
AWS Lambda
AWS Lambda
Amazon Comprehend
AWS Cloud2. Generating
Custom Tags
1. Generating Intents
from Raw Documents
HSBC Policy
Documents
Amazon Simple
Storage Service (S3)
AWS Lambda Amazon EC2
Pre trained deep
learning model
Amazon Lex
AWS Cloud
62. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.S U M M I T
1. User Interface
AWS Cloud
Solution Overview: Fulfilling end-user queries
AWS LambdaAmazon Lex
3. Guided workflows based fulfillment
Amazon DynamoDB
2. Rule-based fulfillment
AWS Lambda Amazon DynamoDB
4. Deep Search based fulfillment
AWS Lambda
Amazon
DynamoDB
HSBC
Users
Web UI
Amazon API Gateway
AWS Elastic Search
Amazon Translate
5. Multi-lingual advice delivery
AWS Lambda
63. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.S U M M I T
Technical challenges overcome
Policy Ingestion
and Tagging
1 2 3
Workflow-based
Fulfillment for
Users Unsure of
Questions
Governance, Audit
and User
Scalability
64. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.S U M M I T
What’s next?
Scale
• Opening up the Assistant capability in more markets and for more policies
Ecosystem
• Virtual Assistant ecosystem with effective orchestration of queries across multiple
use-cases
Data Insights
• Into internal information demands through machine learning & analysis across the
Virtual Assistant data estate
• Incorporating more machine learning algorithms to increase sophistication of the
Virtual Assistants
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Thank You