© 2017, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Timothee Cruse – Solutions Architect March 23, 2017 IoT, Robotics and AI FSI Trends and how they are Transforming the industry
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© 2017, Amazon Web Services, Inc. or its Affiliates. All rights reserved.
Timothee Cruse – Solutions Architect
March 23, 2017
IoT, Robotics and AIFSI Trends and how they are Transforming the industry
How to get there?
http://www.iritech.com/blog/wp-content/uploads/2016/10/IoT.jpg
AWS customers are connecting physical
things to the cloud in every industry
Healthcare and Life
Sciences
Municipal
Infrastructure
Smart Home Retail
Manufacturing, Logistics &
Supply Chain
Agriculture Education Automotive
Impact of IoT
Cost SavingsReduces costs, optimize use of resources, allows for real-time
feedback
Efficiency Fine-tune practices and innovate novel services based on data
Decision
MakingEnables real-time decision making
Improved
InnovationImproved citizen service delivery based on data, e.g. improved traffic
flow, water management, safer pedestrian traffic
https://www.wired.com/2014/12/oscar-misfit/
https://www.jhrewardslife.com/
Capital One Embracing mobile and IoT to improve personal banking
AI
Data Flywheel
Machine Learning
Deep Learning
AI
More Users Better Products
More Data Better Analytics
Object Storage
Databases
Data warehouse
Streaming analytics
BI
Hadoop
Spark/Presto
Elasticsearch
Click stream
User activity
Generated content
Purchases
Clicks
Likes
Sensor data
https://blogs.nvidia.com/blog/2016/07/29/whats-difference-artificial-intelligence-machine-learning-deep-learning-ai/
What’s the Difference?
Internal only – do not distribute
Amazon AIIntelligent Services Powered By Deep Learning
Amazon AI
Intelligent Services Powered By Deep Learning
Amazon AI: New Deep Learning Services
Life-like Speech
Polly LexConversational
Engine
RekognitionImage Analysis
Deep Learning
FrameworksMXNet, TensorFlow,
Theano, Caffe, Torch
DIY Deep Learningfor Custom Models
AI EnabledManaged APIServices
Amazon AI: New Deep Learning Services
Polly LexRekognition
Deep Learning
FrameworksMXNet, TensorFlow, Theano, Caffe, Torch
CO
NT
RO
LU
SA
BIL
ITY
&
SIM
PL
ICIT
Y
Origin
Destination
Departure Date
Flight Booking
“Book a flight
to London”
Automatic
Speech RecognitionNatural Language
Understanding
Book Flight
London
Utterances
Flight booking
London Heathrow
Intent /
Slot model
London Heathrow
Origin
Destination
Departure Date
Flight Booking
“Book a flight
to London”
Automatic
Speech RecognitionNatural Language
Understanding
Book Flight
London
Utterances
Flight booking
London Heathrow
Intent /
Slot model
London Heathrow
LocationLocation
Seattle
Origin
Destination
Departure Date
Flight Booking
“Book a flight
to London”
Automatic
Speech RecognitionNatural Language
Understanding
Book Flight
London
Utterances
Flight booking
London Heathrow
Intent /
Slot model
London Heathrow
LocationLocation
Seattle
Prompt
“When would you like to fly?”
“When would you
like to fly?”
Polly
Origin
Destination
Departure Date
Flight Booking
London Heathrow
Seattle
Prompt
“When would you like to fly?”
“When would you
like to fly?”
Polly
“Next Friday”
Origin
Destination
Departure Date
Flight Booking
“Next Friday”Automatic
Speech Recognition
Next Friday
Utterances
Natural Language
Understanding
Flight booking
02 / 24 / 2017
Intent /
Slot model
London Heathrow
Seattle
02/24/2017
Origin
Destination
Departure Date
Flight Booking
“Next Friday”Automatic
Speech Recognition
Next Friday
Utterances
Natural Language
Understanding
Flight booking
02 / 24 / 2017
Intent /
Slot model
London Heathrow
Seattle
02/24/2017
Confirmation
“Your flight is booked for next Friday”
“Your flight is booked
for next Friday”
Polly
Calculating risk
Amazon RekognitionDeep learning-based image recognition service
Search, verify, and organize millions of images
Object and Scene
DetectionFacial
Analysis
Face
Comparison
Facial
Recognition
FSI Retail use-cases
• Login
• Greeting
• Whitelists / Blacklists
Object and Scene Detection
Generate labels for thousands of objects, scenes, and
concepts, each with a confidence score
• Satellite imagery
• Risk exposure on assets
Maple
Plant
Villa
Garden
Water
Swimming Pool
Tree
Potted Plant
Backyard
Media Case Study
Identify who is on camera at what time for each of 8 networks
so that recorded video streams can be indexed and searched
Video frame-sampling facial recognition solution using
Amazon Rekognition:
• Indexed 97,000 people into a face collection in 1 day
• Sample frames every 6 secs and test for image variance
• Upload images to S3 and call Rekognition to find best facial match
• Store time stamp and faceID metadata
Robots
”
“ • Startup needed a highly scalable online platform
with built-in security and compliance
• Uses AWS products to run its mobile platform,
execute trades, and perform analytics
• Scaled quickly to manage billions of transactions
• Operates business with just two DevOps
employees
• Meets strict compliance and security standards
using AWS
No-Fee Trading Service on AWS
Robinhood is a startup offering a no-fee stock trading
platform. It is based in Palo Alto, California.
By using AWS, Robinhood
has been able to build
incredibly sophisticated systems
with a very small team.
Miles Wellesley
Head of Business Development
”
“
”
“• Startup that saw the opportunity to disrupt
an industry where face-to-face interactions weren’t needed and cumbersome.
• When deploying for new customers, Bambu chooses to run on AWS because of security, agility (time-to-market), scalability and cost efficiency
• Meets strict compliance and security standards using AWS
• Worked hand in hand with AWS to get through the regulatory approval processes in each markets
: The Robo Advisor for SPENDERS, SAVERS & INVESTORS
AWS is not just our technology
platform, they partner closely with us to
help meet our risk and regulatory
requirements.
Aki Ranin
Co-founder and COO
Demo?
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