Introduction to Artificial Intelligence on AWS
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This document provides an overview of artificial intelligence and machine learning services available on Amazon Web Services. It discusses how AI can power applications through services like Amazon Polly for text-to-speech, Amazon Lex for conversational interfaces, Amazon Rekognition for image and video analysis, and Amazon's deep learning platforms. It also provides examples of how customers in various industries like media, public safety, and marketing are using these AWS AI services.
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Introduction to Artificial Intelligence on AWS
- 1. © 2016, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Shankar Ramachandran Solutions Architect Apr 6 2017 Introduction to Artificial Intelligence on AWS
- 2. A Flywheel For Data 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
- 3. Machine Learning & Artificial Intelligence Big Data More Users Better Products More Data Better Analytics A Flywheel For Data
- 4. Algorithms Data Programming Models GPUs & Acceleration The Advent of Deep Learning image understanding natural language processing speech recognition autonomy
- 5. AI Applications on AWS Zillow • Zestimate (using Apache Spark) Howard Hughes Corp • Lead scoring for luxury real estate purchase predictions FINRA • Anomaly detection, sequence matching, regression analysis, network/tribe analysis Netflix • Recommendation engine Pinterest • Image recognition search Fraud.net • Detect online payment fraud DataXu • Leverage automated & unattended ML at large scale (Amazon EMR + Spark) Mapillary • Computer vision for crowd sourced maps Hudl • Predictive analytics on sports plays Upserve • Restaurant table mgmt & POS for forecasting customer traffic TuSimple • Computer Vision for Autonomous Driving Clarifai • Computer Vision APIs
- 6. AI Applications on AWS Pinterest Lens Netflix Recommendation Engine
- 7. Thousands Of Employees Across The Company Focused on AI Discovery & Search Fulfilment & Logistics Enhance Existing Products Define New Product Categories Bring Machine Learning To All Artificial Intelligence At Amazon
- 8. Artificial Intelligence At Amazon (1995)
- 10. Can We Help Customers Put Intelligence At The Heart Of Every Application & Business?
- 11. Amazon AI Intelligent Services Powered By Deep Learning
- 12. Amazon AI: New Deep Learning Services Life-like Speech Polly Lex Conversational Engine Rekognition Image Analysis Deep Learning Frameworks MXNet, TensorFlow, Theano, Caffe, Torch
- 13. 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
- 14. One-Click GPU Deep Learning AWS Deep Learning AMI Up to~40k CUDA cores MXNet TensorFlow Theano Caffe Torch Pre-configured CUDA drivers Anaconda, Python3 + CloudFormation template + Container Image
- 15. MXNet: Scalable Deep Learning Framework
- 16. Converts text to life-like speech 47 voices 24 languages Low latency, real time Fully managed Polly: Life-like Speech Service Voice Quality & Pronunciation 1. Automatic, Accurate Text Processing 2. Intelligible and Easy to Understand 3. Add Semantic Meaning to Text 4. Customized Pronunciation Articles and Blogs Training Material Chatbots (Lex) Public Announcements
- 17. 1st Gen: Machine-oriented interactions 2nd Gen: Control-oriented & translated 3rd Gen: Intent-oriented The Advent Of Conversational Interactions
- 18. Voice & Text “Chatbots” Powers Alexa Voice interactions on mobile, web & devices Text interaction with Slack & Messenger Enterprise Connectors (with more coming) Salesforce Microsoft Dynamics Marketo Zendesk Quickbooks Hubspot Lex: Build Natural, Conversational Interactions In Voice & Text Improving human interactions… • Contact, service, and support center interfaces (text + voice) • Employee productivity and collaboration (minutes into seconds)
- 19. 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
- 20. 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
- 21. 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
- 22. 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”
- 23. 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
- 24. 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
- 25. 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 Hotel Booking
- 26. 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 Integrated with S3, Lambda, Polly, Lex
- 27. Object and Scene Detection Generate labels for thousands of objects, scenes, and concepts, each with a confidence score • Search, filter, and curate image libraries • Smart searches for user generated content • Photo, travel, real estate, vacation rental applications Maple Plant Villa Garden Water Swimming Pool Tree Potted Plant Backyard
- 28. Facial Analysis Locate faces within images and analyze face attributes to detect emotion, pose, facial landmarks, and features • Avoid faces when cropping images and overlaying ads • Capture user demographics and sentiment • Recommend the best photos • Improve online dating match recommendations • Dynamic, personalized ads
- 29. Face Comparison Measure the likelihood that faces in two images are of the same person • Add face verification to applications and devices • Extend physical security controls • Provide guest access to VIP-only facilities • Verify users for online exams and polls
- 30. Facial Recognition Identify people in images by finding the closest match for an input face image against a collection of stored face vectors • Add friend tagging to social and messaging apps • Assist public safety officers find missing persons • Identify employees as they access sensitive locations • Identify celebrities in historical media archives
- 31. 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
- 32. Influencer Marketing Case Study Associate influencers with objects and scenes in social media images in order to create high impact campaigns for clients Using Rekognition for metadata extraction: • Create rich media indexes of images from social media feeds, which the application associates with influencers • Enable analytics to profile environments where influence is strongest • Connect client brands with the influencers most likely to have impact
- 33. Rekognition Customers Media and Entertainment Public Safety Law Enforcement Digital Asset Management Influencer Marketing Digital Advertising Education Consumer Storage
- 34. Amazon AI Services • Leveraging Amazon internal experiences with AI / ML • Managed API services with embedded AI for maximum accessibility and simplicity • Full stack of platforms and engines for specialized deep learning applications
Editor's Notes
- Introducing Amazon Rekognition - a fully managed deep learning based image recognition service. Rekognition was designed from the get-go to run at scale. It comprehends scenes, objects, concepts and faces. Given an image, it will return a list of labels. Given an image with one or more faces,it will return bounding boxes for each face, along with face attributes. Given two images with faces, it will compare the largest face from the source image and find similarity with faces found in the tagret image. Rekognition provides quality face recognition at scale, and supports creation of collection of millions of faces and search of similar faces in the collection. Now lets dive into each of these features and look at the API that support these features.
- Clients can request influencers in a key demographic. Rekognition partners use their metadata to identify high quality influencers for targeted campaigns, which may involve paying influencers for product use and social media posts featuring the product. An influencer’s strength is measured by who is following them on social media Future use for Reko: identify brands, measure impact, rate influencers