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An Introduction to Amazon AI Services
This document provides an introduction to Amazon's artificial intelligence services, including Amazon Polly for text-to-speech, Amazon Rekognition for image and video analysis, and Amazon Lex for conversational interactions. It discusses how these services are powered by deep learning and machine learning techniques and are built to be high quality, easy to use, and cost effective.
An Introduction to Amazon AI Services
- 1. © 2017, AmazonWeb Services, Inc. or its Affiliates. All rights reserved. Roland Keijzer - CTO Bynder Dinah Barrett – AWS Solutions Architect An Introduction to Amazon AI Services June 28, 2017
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- 3. Running AI InProduction on AWS Today
- 4. Artificial Intelligence AtAmazon Thousands Of Employees Across The Company Focused on AI Discovery & Search Fulfilment & Logistics Enhance Existing Products Define New Categories Of Products Bring Machine Learning To All
- 5. The Advent Of DeepLearning Algorithms Data GPUs & Acceleration Programming models AWS
- 6. Amazon AI Intelligent ServicesPowered By Deep Learning
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- 8. Introducing Amazon AI Polly Text-to-Speech Rekognition ImageAnalysis Lex ASR & NLU Apache MXNet Apache Deep learning framework aws.amazon.com/amazon-ai
- 9. Apache MXNet Programmable PortableHigh Performance Near linear scaling across hundreds of GPUs Highly efficient models for mobile and IoT Simple syntax, multiple languages
- 10. Why Apache MXNet? MostOpen Best On AWS Optimized for deep learning on AWS Accepted into the Apache Incubator (Integration with AWS)
- 11. One-Click Deep Learning AWS DeepLearning AMIs Amazon Linux & Ubuntu Up to~40k CUDA cores Apache MXNet TensorFlow Theano Keras Caffe CNTK Torch Pre-configured CUDA drivers Anaconda, Python3 Out-of-the-box Tutorials + CloudFormation template + Container Image Available in the AWS Marketplace
- 12. Introducing Amazon AI Polly Text-to-Speech ApacheMXNet Rekognition Image Analysis Lex ASR & NLU Apache Deep learning framework aws.amazon.com/amazon-ai
- 13. Amazon Polly: Life-likeSpeech Service Converts text to life-like speech 47 voices 24 languages Low latency, real time Fully managed
- 14. “Today in Londonit’s 25 °C” 1. Automatic, Accurate Text Processing Polly: A Focus On Voice Quality & Pronunciation
- 15. Polly: A FocusOn Voice Quality & Pronunciation 2. Intelligible and Easy to Understand 1. Automatic, Accurate Text Processing She sells sea shells by the sea shore. The shells she sells are surely seashells. So if she sells shells on the seashore, I'm sure she sells seashore shells
- 16. 2. Intelligible andEasy to Understand 3. Add Semantic Meaning to Text “Dinah’s number is "07867123123” “Dinah’s number is "07867123123” Telephone Number Polly: A Focus On Voice Quality & Pronunciation 1. Automatic, Accurate Text Processing
- 17. 2. Intelligible andEasy to Understand 3. Add Semantic Meaning to Text 4. Customized Pronunciation “My son’s name is Jay.” Polly: A Focus On Voice Quality & Pronunciation 1. Automatic, Accurate Text Processing “My son’s name is Jay.”
- 18. Amazon Polly: Life-likeSpeech Service High quality, through best-in-class deep learning Deep functionality Easy to use & thoughtfully integrated Built for production Low Cost (free tier) Upload your own text through the console and start using Amazon Polly today! https://aws.amazon.com/polly
- 19. Introducing Amazon AI Polly Text-to-Speech ApacheMXNet Rekognition Lex Image Analysis ASR & NLU Apache Deep learning framework aws.amazon.com/amazon-ai
- 20. Rekognition: Search &Understand Visual Content Real-time & batch image analysis Object & Scene Detection Facial Detection Face SearchFacial Analysis
- 21. Rekognition: Object &Scene Detection Bay Beach Coast Outdoors Sea Water Palm_tree Plant Tree Summer Landscape Nature Hotel 99.18% 99.18% 99.18% 99.18% 99.18% 99.18% 99.21% 99.21% 99.21% 58.3% 51.84% 51.84% 51.24% Category Confidence
- 22. Rekognition: Facial Detection Emotion:calm: 73% Sunglasses: false (value: 0) Mouth open wide: 0% (value: 0) Eye closed: open (value: 0) Age: 28.57 (value: 28.57) Glasses: no glass (value: 0) Mustache: false (value: 0) Beard: no (value: 0)
- 23. Demographic Data Facial Landmarks SentimentExpressed Image Quality Facial Analysis Brightness: 25.84 Sharpness: 160 General Attributes Rekognition: Facial Analysis
- 24. Amazon Rekognition: FacialSearch Facial verification Face Search Visual Similarity Search (compare two faces) (compare many faces) (find similar faces)
- 25. High quality, through best-in-class deep learning Deep functionality Easyto use & thoughtfully integrated Built for production Low Cost (free tier) Rekognition: Search & Understand Visual Content https://aws.amazon.com/rekognition
- 26. Introducing Amazon AI Polly Text-to-Speech ApacheMXNet Rekognition Lex Image Analysis ASR & NLU Apache Deep learning framework aws.amazon.com/amazon-ai
- 27. The Advent OfConversational Interactions 1st Gen: Machine-oriented interactions 2nd Gen: Control-oriented & translated 3rd Gen: Intent-oriented
- 28. Lex: Build Natural,Conversational Interactions In Voice & Text Voice & Text “Chatbots” Powers Alexa Voice interactions on mobile, web & devices Text interaction with Slack, FB Messenger and Twilio Enterprise Connectors Salesforce Microsoft Dynamics Marketo Zendesk Quickbooks Hubspot
- 29. High quality, through best-in-class deep learning Deep functionality Easyto use & thoughtfully integrated Built for production Low Cost (free tier) Lex: Build Natural, Conversational Interactions In Voice & Text https://aws.amazon.com/lex Build your bot with Amazon Lex!
- 30. Amazon Lex -Technology Amazon Lex Automatic Speech Recognition (ASR) Same technology that powers Alexa Cognito CloudTrail CloudWatch AWS Services Action AWS Lambda Authentication & Visibility Speech API Language API Fulfillment End-Users Developers Console SDK Intents, Slots, Prompts, Utterances Input: Speech or Text Multi-Platform Clients: Mobile, IoT, Web, Chat API Response: Speech (via Polly TTS) or Text Natural Language Understanding (NLU)
- 31. Amazon AI: What’sNext? Polly Text-to-Speech Apache MXNet Deep learning framework Rekognition Lex Image Analysis ASR & NLU New APIs and tools Apache
- 36. 1984 15 GB/mo 1994 29 TB/mo 2004 1.3EB/mo 2014 42 EB/mo
- 51. References • AWS AIBlog • Getting Started with Amazon Polly • Getting Started with Amazon Lex • Getting Started with Amazon Rekognition • Getting Started with Deep Learning
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