AI for developers
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The document discusses Amazon Web Services machine learning services including Amazon Rekognition (image and video analysis), Amazon Polly (text-to-speech), Amazon Transcribe (speech recognition), Amazon Comprehend (natural language processing), and Amazon Translate (machine translation). It provides examples of how developers can use these services to build applications that see, hear, speak, understand and translate content. The services are part of AWS's aim to put machine learning in the hands of every developer.
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AI for developers
- 1. © 2018, Amazon Web Services, Inc. or Its Affiliates. All rights reserved. AI for Developers Julien Simon Principal Evangelist, Artificial Intelligence & Machine Learning @julsimon 11/06/2018
- 2. © 2018, Amazon Web Services, Inc. or Its Affiliates. All rights reserved. Amazon.com,1995
- 3. © 2018, Amazon Web Services, Inc. or Its Affiliates. All rights reserved. « Two Decades of Recommender Systems at Amazon.com » (2017) https://www.computer.org/csdl/mags/ic/2017/03/mic2017030012.html G.D. Linden, J.A. Jacobi, and E.A. Benson, Collaborative Recommendations Using Item-to-Item Similarity Mappings, US Patent 6,266,649, to Amazon.com, Patent and Trademark Office, 2001 (filed 1998).
- 4. © 2018, Amazon Web Services, Inc. or Its Affiliates. All rights reserved.
- 5. © 2018, Amazon Web Services, Inc. or Its Affiliates. All rights reserved.
- 6. © 2018, Amazon Web Services, Inc. or Its Affiliates. All rights reserved.
- 7. © 2018, Amazon Web Services, Inc. or Its Affiliates. All rights reserved.
- 8. © 2018, Amazon Web Services, Inc. or Its Affiliates. All rights reserved. Put Machine Learning in the hands of every developer Our mission
- 9. © 2018, Amazon Web Services, Inc. or Its Affiliates. All rights reserved. More ML is built on AWS than anywhere else
- 10. © 2018, Amazon Web Services, Inc. or Its Affiliates. All rights reserved. More ML is built on AWS than anywhere else
- 11. © 2018, Amazon Web Services, Inc. or Its Affiliates. All rights reserved. Application Services Platform Services Frameworks & Infrastructure API-driven services: Vision, Language & Speech Services, Chatbots Deploy machine learning models with high-performance machine learning algorithms, broad framework support, and one-click training, tuning, and inference. Develop sophisticated models with any framework, create managed, auto- scaling clusters of GPUs for large scale training, or run prediction on trained models. The AWS ML Stack
- 12. © 2018, Amazon Web Services, Inc. or Its Affiliates. All rights reserved. Amazon Rekognition Deep Learning-based image analysis service
- 13. Amazon Rekognition Image Object and Scene Detection Facial Analysis Face Recognition Text in ImageUnsafe Image Detection Celebrity Recognition Face Comparison
- 14. © 2018, Amazon Web Services, Inc. or Its Affiliates. All rights reserved. Object & Scene Detection
- 15. © 2018, Amazon Web Services, Inc. or Its Affiliates. All rights reserved. Facial Analysis
- 16. © 2018, Amazon Web Services, Inc. or Its Affiliates. All rights reserved. Crowd Detection – up to 100 faces
- 17. © 2018, Amazon Web Services, Inc. or Its Affiliates. All rights reserved. Facial Search
- 18. © 2018, Amazon Web Services, Inc. or Its Affiliates. All rights reserved. Explicit Nudity Nudity Graphic Male Nudity Graphic Female Nudity Sexual Activity Partial Nudity Suggestive Female Swimwear or Underwear Male Swimwear or Underwear Revealing Clothes Image Moderation
- 19. © 2018, Amazon Web Services, Inc. or Its Affiliates. All rights reserved. Celebrity Recognition
- 20. © 2018, Amazon Web Services, Inc. or Its Affiliates. All rights reserved. Text in Image
- 21. © 2018, Amazon Web Services, Inc. or Its Affiliates. All rights reserved. Amazon Rekognition Video Deep Learning-based video analysis service
- 22. Amazon Rekognition Video Analyze activity, recognize, and track people in stored and live video Object and activity detection Person tracking Face recognition Real-time live stream Unsafe video detection Celebrity recognition Facial Analysis
- 23. © 2018, Amazon Web Services, Inc. or Its Affiliates. All rights reserved. Sky News used Amazon Rekognition to perform real-time identification of guests as they entered St. George’s Chapel
- 24. © 2017, Amazon Web Services, Inc. or its Affiliates. All rights reserved.
- 25. © 2017, Amazon Web Services, Inc. or its Affiliates. All rights reserved.
- 26. © 2017, Amazon Web Services, Inc. or its Affiliates. All rights reserved.
- 27. Use case: real-time video identification Live Street Camera Amazon Kinesis Video Streams Amazon Rekognition Video Face collection 1. Camera-captured video streams are processed by Kinesis Video Streams 2. Amazon Rekognition Video analyses the video and searches faces on screen against a collection of millions of faces User 3. User is notified in case of face matches Amazon SNS AWS Lambda Amazon Kinesis Streams
- 28. © 2018, Amazon Web Services, Inc. or Its Affiliates. All rights reserved. DEMO https://aws.amazon.com/blogs/machine-learning/easily-perform-facial-analysis-on-live-feeds-by- creating-a-serverless-video-analytics-environment-with-amazon-rekognition-video-and-amazon- kinesis-video-streams
- 29. © 2018, Amazon Web Services, Inc. or Its Affiliates. All rights reserved. Amazon Polly Deep Learning-based text-to-speech service
- 30. © 2018, Amazon Web Services, Inc. or Its Affiliates. All rights reserved. Turn text into lifelike speech using Deep Learning Wide selection of voices and languages Synchronize speech Fine-grained control Unlimited replay Amazon Polly
- 31. © 2018, Amazon Web Services, Inc. or Its Affiliates. All rights reserved. <speak xml:lang="en-US"> The price of this book is <prosody rate="60%">45€</prosody> </speak> Support for Speech Synthesis Markup Language (SSML) Version 1.0 https://www.w3.org/TR/speech-synthesis A Focus on Voice Quality
- 32. © 2018, Amazon Web Services, Inc. or Its Affiliates. All rights reserved. DEMO: breathing effect
- 33. © 2018, Amazon Web Services, Inc. or Its Affiliates. All rights reserved. Amazon Translate Neural Machine Translation Service Now generally available
- 34. © 2018, Amazon Web Services, Inc. or Its Affiliates. All rights reserved. Amazon Translate Natural and fluent language translation Real-time translation Batch analysis Automatic language recognition Low cost
- 35. Languages Available now English to/from: • Spanish • Portuguese • German • French • Arabic • Simplified Chinese Coming soon • Japanese • Russian • Italian • Traditional Chinese • Turkish • Czech
- 36. © 2018, Amazon Web Services, Inc. or Its Affiliates. All rights reserved. DEMO
- 37. © 2018, Amazon Web Services, Inc. or Its Affiliates. All rights reserved. Amazon Transcribe Automatic speech recognition service Now generally available
- 38. © 2018, Amazon Web Services, Inc. or Its Affiliates. All rights reserved. Amazon Transcribe Automatic conversion of speech into accurate, grammatically correct text Support for telephony audio Timestamp generation Intelligent punctuation and formatting Recognize multiple speakers Custom vocabulary Multiple languages
- 39. © 2018, Amazon Web Services, Inc. or Its Affiliates. All rights reserved. Amazon Comprehend Natural Language Processing
- 40. © 2018, Amazon Web Services, Inc. or Its Affiliates. All rights reserved. Fully managed natural language processing Discover valuable insights from text Entities Key Phrases Language Sentiment Amazon Comprehend
- 41. © 2018, Amazon Web Services, Inc. or Its Affiliates. All rights reserved. DEMO Rekognition + Polly + Comprehend + Translate
- 42. © 2018, Amazon Web Services, Inc. or Its Affiliates. All rights reserved. https://medium.com/@julsimon/johnny-pi-i-am-your-father-part-8-reading-translating-and-more-c22f7b8275cc
- 43. © 2018, Amazon Web Services, Inc. or Its Affiliates. All rights reserved. FRAMEWORKS AND INTERFACES PLATFORM SERVICES APPLICATION SERVICES Amazon Rekognition Amazon Polly Amazon Lex Democratization of ML Amazon Rekognition Video Amazon Transcribe Amazon Comprehend Amazon SageMaker AWS DeepLens Deep Learning AMI Amazon Translate
- 44. © 2018, Amazon Web Services, Inc. or Its Affiliates. All rights reserved. Thank you! Julien Simon Principal Evangelist, Artificial Intelligence & Machine Learning @julsimon https://aws.amazon.com/machine-learning https://aws.amazon.com/blogs/ai https://medium.com/@julsimon https://youtube.com/juliensimonfr https://gitlab.com/juliensimon/johnnypi
Editor's Notes
- Amazon Robotics was founded in 2003 on the notion that in order to meet consumer demands in eCommerce, a better approach to order fulfillment solutions was necessary. Amazon Robotics empowers a smarter, faster, more consistent customer experience through automation automates fulfilment center operations using various methods of robotic technology including autonomous mobile robots, sophisticated control software, language perception, power management, computer vision, depth sensing, machine learning, object recognition, and semantic understanding of commands.
- Amazon Echo is a hands-free speaker you control with your voice. Echo connects to the Alexa Voice Service to play music, make calls, send and receive messages, provide information, news, sports scores, weather, and more—instantly. All you have to do is ask.
- Amazon Prime Air is a service that will deliver packages up to 2.5 kg in 30 minutes or less using small drones and relies extensively on visual object recognition. We have Prime Air development centers in the United States, the United Kingdom, Austria, France and Israel.
- Amazon Go is a new kind of store with no checkout required. We created the world’s most advanced shopping technology so you never have to wait in line. With our Just Walk Out Shopping experience, simply use the Amazon Go app to enter the store, take the products you want, and go! No lines, no checkout. (No, seriously.) No lines, no checkout Our checkout-free shopping experience is made possible by the same types of technologies used in self-driving cars: computer vision, sensor fusion, and deep learning. Our Just Walk Out Technology automatically detects when products are taken from or returned to the shelves and keeps track of them in a virtual cart. When you’re done shopping, you can just leave the store. Shortly after, we’ll charge your Amazon account and send you a receipt.
- Let’s take a look at what Rekognition Image can do and how it has evolved over the past year Last re:Invent we launched Rekognition with Face detection, Face recognition and Object and Scene Detection In April, we added Unsafe Image detection. . In June, we launched Celebrity Recognition. In November, we launched Text In Image. And we also updated Face Detection, added real-time Face recognition, and updated our Moderation models …and we are continually improving based on customer feedback.
- You can use the ‘MinConfidence’ parameter in your API requests to balance detection of content (recall) vs the accuracy of detection (precision).
- You can use the ‘MinConfidence’ parameter in your API requests to balance detection of content (recall) vs the accuracy of detection (precision).
- We heard a need from customers they would like to have a deep learning-based Video analysis service Introducing Amazon Rekognition Video: a deep learning-based video recognition and analysis service for live or stored video that offers: Object and Activity Detection: With Rekognition Video, you can detect thousands of objects and activities accurately, and extract motion-based context from a video. For example, your application can quickly analyze a consumer video of a baby's first walk, and generate labels like "baby”, "crawling”, "falling”, and "hugging” with timestamps and confidence scores. This allows you to generate search indexes for consumer video archives. Person Tracking: With Rekognition Video motion-based video analysis capabilities, you can track people through the video even when their faces are not visible, or as the whole person might go in and out of the scene. This makes investigation and monitoring of individuals easy and accurate. Face Recognition: Rekognition Video allows you to identify persons from a large existing collection of faces. This allows you to build applications that locate a Person of Interest in real time from a live stream or in batch from Amazon S3. Streaming mode by native integration with Amazon Kinesis Video Streams: In streaming mode, the face detection and recognition APIs natively integrate with video stream from Kinesis Video Streams to provide output at low latency. Kinesis Video Streams enables developers to transmit thousands of live feeds and associated metadata to persist them on Amazon S3 and Glacier. Unsafe Video Detection: Rekognition Video enables easy filtering of video for explicit and suggestive content, providing fine-grained detection of labels associated with inappropriate / NSFW content at a video frame level. Celebrity Recognition: With Rekognition Video, you can detect and recognize celebrities in a video and track in which video frames each of them appears. This allows you to index and search digital video libraries for celebrities based on your particular interest. Feature capabilities summary: Contextual insight - motion and real-time Fully managed, scalable, and easy-to-use video analysis service Deep learning-based -> Continuously improving Integrated with Amazon S3, Amazon Kinesis Video Streams, AWS Lambda – get started with video analysis right out-of-the-box
- Polly also support Speech Synthesis Markup Language (SSML) Version 1.0 The Voice Browser Working Group has sought to develop standards to enable access to the Web using spoken interaction.
- You have customers all over the world who speak several different languages, so you want to translate it into a lot of different languages. Here again, the way that people have traditionally solved this problem is that they've hired translation agencies, which are expensive and time-consuming. They only pick out their most-important pieces to do, and they leave all that value on the table. Amazon Translate, which automatically translates text between languages, helps to solve this problem. Translate is great for use cases that require real-time translation. These are things like live customer support or business communications with social media. You can also translate an entire bucket at one time in a batch operation. Soon, you’ll be able to use the service to recognize the source language on the fly, so you don't even have to specify what language you're trying to translate from. And like all our other services, you will find this to be very cost-effective.
- One of the things that's been interesting is that there's so much data now that's being locked up in audio and video files. The problem is that it’s really hard to search audio well. The best way to do it is to convert it from audio to text. Traditionally how people have done this is that they've hired manual transcription agencies. They're expensive and they're time-consuming. So people typically only pick out the very most important things they want to transcribe, and they leave all the rest on the table. All this data and all this value is sitting out there, not being taken advantage of and leveraged. Amazon Transcribe solves this problem. Transcribe does long-form automatic speech recognition. It can analyze any WAV or MP3 audio file and return text. It's super-useful for all kinds of things, like call logs and subtitles for videos or capturing what's said in a presentation or a meeting. We‘ve started with English and Spanish, but we'll have many more languages coming soon. One of the things that we do with this service which is different from other transcription services is it won't show up to you as just one long, uninterrupted string of text like you'll find in other transcription services. Instead, we use machine learning to add in punctuation and grammatical formatting so the text you get back is immediately usable. Then we time-stamp every word so you can align subtitles to the video so that it's much easier to index. The service supports high-quality audio, but also because so much of the audio data today is generated from phones, you have to be able to deal with lower-quality, low-bit-rate audio. And we uniquely support that as well. Very soon, you’ll also be able to distinguish between multiple speakers, and add your own custom libraries and vocabularies because there are certain words that you may use in a different way than others that you want the service to understand so it could be used quickly the way you mean it.
- …Amazon Comprehend, a Natural Language Processing service that enables customers to discover insights from text. 1/ Without provisioning a server, Comprehend can understand documents, social network posts, articles, and any other data in AWS 2/ Simply provide text stored in data lake in S3 via Comprehend API, and Comprehend uses NLP to give you highly accurate info about what it contains in 4 categories: a/ entities (people, places, dates, brands, qtys) b/ key phrases that provide significance to the text c/ language being used d/ sentiment
- 1/ Comprehend also has the unique ability to not just look at a single document at a time but to look at millions in order to identify the topics within these docs—we call this TOPIC MODELING 2/ Publisher org articles by subject matter; healthcare by symptom or diagnosis 3/ Comprehend does this in an incredibly efficient manner…For ex, for 300 docs, each around 1MB in size, Comprehend can build a custom topic model in 45 mins for $1.80 4/ Makes it much easier and cost effective to build more intelligent models and actions out of all this data sitting in text 1/ Comprehend also has the unique ability to not just look at a single document at a time but to look at millions in order to identify the topics within these docs—we call this TOPIC MODELING 2/ Publisher org articles by subject matter; healthcare by symptom or diagnosis 3/ Comprehend does this in an incredibly efficient manner…For ex, for 300 docs, each around 1MB in size, Comprehend can build a custom topic model in 45 mins for $1.80 4/ Makes it much easier and cost effective to build more intelligent models and actions out of all this data sitting in text
- So far, we've discussed the bottom and middle layers of the machine learning stack – first we talked about the frameworks and the deep learning AMI for expert practitioners. Then, SageMaker and DeepLens in the middle layer to bring ML capabilities to all developers. Now, at the top of the stack, we serve developers and companies who want to add solution-oriented intelligence to their applications through an API call rather than developing and training their own models. These are services that exhibit artificial intelligence that emulates a human’s cognitive skills. Last year, we announced three services in this area: Amazon Rekognition (image analysis), Amazon Polly (text-to-speech), and Amazon Lex (conversational applications).