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Innovation with AWS: IoT, Robotics and AI

  1. © 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
  2. How to get there?
  3. http://www.iritech.com/blog/wp-content/uploads/2016/10/IoT.jpg
  4. 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
  5. Impact of IoT Cost Savings Reduces costs, optimize use of resources, allows for real-time feedback Efficiency Fine-tune practices and innovate novel services based on data Decision Making Enables real-time decision making Improved Innovation Improved citizen service delivery based on data, e.g. improved traffic flow, water management, safer pedestrian traffic
  6. https://www.wired.com/2014/12/oscar-misfit/
  7. https://www.jhrewardslife.com/
  8. Capital One Embracing mobile and IoT to improve personal banking
  9. AI
  10. 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
  11. https://blogs.nvidia.com/blog/2016/07/29/whats-difference-artificial-intelligence-machine-learning-deep-learning-ai/ What’s the Difference?
  12. Internal only – do not distribute Amazon AI Intelligent Services Powered By Deep Learning
  13. Amazon AI Intelligent Services Powered By Deep Learning
  14. Amazon AI: New Deep Learning Services Life-like Speech Polly Lex Conversational Engine Rekognition Image Analysis Deep Learning Frameworks MXNet, TensorFlow, Theano, Caffe, Torch
  15. DIY Deep Learning for Custom Models AI Enabled Managed API Services Amazon AI: New Deep Learning Services Polly LexRekognition Deep Learning Frameworks MXNet, TensorFlow, Theano, Caffe, Torch CONTROL USABILITY& SIMPLICITY
  16. Origin Destination Departure Date Flight Booking “Book a flight to London” Automatic Speech Recognition Natural Language Understanding Book Flight London Utterances Flight booking London Heathrow Intent / Slot model London Heathrow
  17. Origin Destination Departure Date Flight Booking “Book a flight to London” Automatic Speech Recognition Natural Language Understanding Book Flight London Utterances Flight booking London Heathrow Intent / Slot model London Heathrow LocationLocation Seattle
  18. Origin Destination Departure Date Flight Booking “Book a flight to London” Automatic Speech Recognition Natural 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
  19. 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”
  20. 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
  21. 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
  22. Calculating risk
  23. Amazon Rekognition Deep learning-based image recognition service Search, verify, and organize millions of images Object and Scene Detection Facial Analysis Face Comparison Facial Recognition
  24. FSI Retail use-cases • Login • Greeting • Whitelists / Blacklists
  25. 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
  26. 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
  27. Robots
  28. ” “ • 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 ” “
  29. ” “ • 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
  30. Demo?
  31. Thank you! tcruse@amazon.com
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