How AI connect dots for IoT
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oT can give you great insight into consumer behaviour and demand, helping to you create the innovative, revenue-generating services of the future. However, there are still lots of challenges around collecting data from devices, which often have significant limitations in terms of processing power, memory and interfaces. In this presentation, Danilo talks about how Amazon AI services can be used to augment device capabilities to make data collection, storage and analytics easier. He also considers how people can start interacting with machines in a more natural way, for example using natural language understanding (NLU), automatic speech recognition (ASR), visual search and image recognition, text-to-speech (TTS). Learning objectives: - Learn how to design IoT solutions using services such as AWS Greengrass and AWS IoT - Gain insights into practical use cases for Amazon AI services - Understand the possibilities of using AI from an IoT device
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How AI connect dots for IoT
- 1. How AI connects the dots for IoT: Augmenting IoT Solutions with Artificial Intelligence Danilo Poccia, Technical Evangelist @danilop
- 2. Credit: Gerry Cranham/Fox Photos/Getty Images http://www.telegraph.co.uk/travel/destinations/europe/united-kingdom/england/london/galleries/The-history-of-the-Tube-in-pictures-150-years-of-London-Underground/1939-ticket-examin/
- 3. 1939 London Underground Credit: Gerry Cranham/Fox Photos/Getty Images http://www.telegraph.co.uk/travel/destinations/europe/united-kingdom/england/london/galleries/The-history-of-the-Tube-in-pictures-150-years-of-London-Underground/1939-ticket-examin/
- 4. 1939 London Underground Credit: Gerry Cranham/Fox Photos/Getty Images http://www.telegraph.co.uk/travel/destinations/europe/united-kingdom/england/london/galleries/The-history-of-the-Tube-in-pictures-150-years-of-London-Underground/1939-ticket-examin/ IoT Big Data Machine Learning
- 5. One of the big challenges with the IoT is to Collect Analyze Act on data from devices to generate insights.
- 6. AWS IoT
- 7. Customer Success – Philips Healthcare IoT on AWS to collect and act on critical data across different devices Philips is a leading health-tech company, working to create a new era of connected and personalized digital health and care.. With the addition of AWS IoT, we will greatly accelerate the pursuit of our vision by making it easy to acquire, process, and act on data from heterogeneous devices in real time. • AWS gives Philips customers greater control of their health with connected digital health solutions that support healthy living and improved care coordination. • HealthSuite, powered by AWS, is a digital platform that manages more than 7 million connected medical-grade, consumer devices, sensors and mobile apps • The Philips HealthSuite digital platform analyzes and stores 15 PB of patient data from 390 million imaging studies, medical records, and patient inputs. • AWS provides the reliability, performance and scalability that Philips needs to help protect patient data which grows by petabyte/month. Jeroen Tas CEO Healthcare Informatics Solutions and Services, Philips ” “
- 8. Customer Success – SONOS Increase the Value of a Product Over Time with Data Telemetry and Usage Data All the music on earth, in every room of your home, wirelessly. Sonos is the smart speaker system that streams all your favorite music to any room, or every room. Control your music with one simple app, and fill your home with pure, immersive sound. “A 10 year old product can do things that hadn’t been invented 10 years ago. Most importantly, going forward, people will expect your product to improve, and if it isn’t being updated and getting better, you’re literally being left behind.” Jon Cotter Sr. Software Development Manager, ” “ • Utilizes AWS to collect, store, and process performance metric data and reports for individual speaker systems. • Can monitor the quality of speakers in the field, and dramatically add new functionality to existing speakers without refreshing hardware. • Launching Trueplay: a Smart Speaker Tuning services that measures the acoustics in any room and fine-tunes your speaker. • Launching in 2015 yet available to devices purchased over 5 years ago
- 9. “We launched Hive towards the end of 2013 and today we have 75,000 customers… The speed at which we delivered Hive is directly related to our decision to use AWS cloud” Seb Chakraborty Head of Web and Platform Design • British Gas started a project called Hive, part of its Connected Homes Strategy. • Hive Active Heating allows users to control heating and hot water remotely from mobile, laptop or smartphones. • Such a flexibility allows users to control heating exactly how they need it and save up to £150 a year on utility bills Customer Success – British Gas Brings central heating control to smartphones with AWS British Gas uses AWS cloud for scaling the project and to deliver API toolsets around it. ” “
- 10. IoT Devices Have Limited Resources On Board
- 11. Challenges Of Devices Living On The Edge Round-trip latency Intermittent connectivity Expensive bandwidth Programming and updating embedded software needs specialized skills Limited to what is on the device unless you rewrite or program the device
- 12. AWS Greengrass: Local Compute, Messaging & Data Caching Local compute Local data caching Secure communications Local messaging
- 13. Benefits of AWS Greengrass Respond to local events quickly Operate offline Simplified device programming Reduce the cost of IoT applications
- 14. Amazon Greengrass: Example Use Cases Smart Homes Agriculture Manufacturing
- 15. AWS Snowball
- 16. How to maximize the capabilities of IoT devices? Usually IoT devices have significant limitations in terms of processing power, memory and interfaces
- 17. Artificial Intelligence & Deep Learning At Amazon Thousands Of Employees Across The Company Focused on AI Discovery & Search Fulfilment & Logistics Add ML-powered features to existing products Echo & Alexa
- 18. Artificial Intelligence on AWS P2, F1 & Elastic GPUs Deep Learning AMI and template Investment in Apache MXNet
- 19. Apache MXNet
- 20. Deep Learning Frameworks MXNet, Caffe, Tensorflow, Theano, Torch, CNTK and Keras Pre-installed components to speed productivity, such as Nvidia drivers, CUDA, cuDNN, Intel MKL-DNN with MXNet, Anaconda, Python 2 and 3 AWS Integration Deep Learning AMI
- 21. Amazon AI Bringing Powerful Artificial Intelligence To All Developers
- 22. Amazon Rekognition Image Recognition And Analysis Powered By Deep Learning 1
- 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 Image Moderation
- 24. Amazon Rekognition: Images In, Categories and Facial Analysis Out Amazon Rekognition Car Outside Daytime Driving Objects & Scenes Female Smiling Sunglasses Face ID DetectLabels DetectFaces DetectModerationLabels CompareFaces IndexFaces SearchFacesByImage Faces
- 26. Bynder allows you to easily create, find and use content for branding automation and marketing solutions. With our new AI capabilities, Bynder’s software… now allows users to save hours of admin labor when uploading and organizing their files, adding exponentially more value. Chris Hall CEO, Bynder ” “ With Rekognition, Bynder revolutionizes marketing admin tasks with AI capabilities
- 27. Artfinder is building a world where artists can make a living doing what they love. While our artists are able to give us descriptions, our users may want to search in ways the artist hasn’t thought of. We use Rekognition to obtain objective labels about an artwork based on its imagery. David Tilleyshort CTO, Artfinder ” “ With both Rekognition and Amazon ML, Artfinder was able to very rapidly prototype advance machine learning techniques, with minimum developer time and no upfront infrastructure costs • A growing catalogue of 300,000 artwork pieces – and visual search a key part of that. • Even though Rekognition was designed to be used for photography, they have been able to get some interesting results across their inventory of paintings, handmade prints, sculptures, collages, drawings and photography.
- 28. Amazon Polly Text To Speech Powered By Deep Learning 2
- 29. Amazon Polly: Text In, Life-like Speech Out Amazon Polly “The temperature in WA is 75°F” “The temperature in Washington is 75 degrees Fahrenheit” 47 voices spread across 24 languages
- 30. TEXT Market grew by > 20%. WORDSPHONEMES { { { { { ˈtwɛn.ti pɚ.ˈsɛnt ˈmɑɹ.kət ˈgɹu baɪ ˈmoʊɹ ˈðæn PROSODY CONTOURUNIT SELECTION AND ADAPTATION TEXT PROCESSING PROSODY MODIFICATIONSTREAMING Market grew by more than twenty percent Speech units inventory
- 31. aws polly synthesize-speech --text "It was nice to live such a wonderful live show." --output-format mp3 --voice-id Joanna --text-type text output.mp3
- 32. Duolingo voices its language learning service Using Polly Duolingo is a free language learning service where users help translate the web and rate translations. With Amazon Polly our users benefit from the most lifelike Text-to-Speech voices available on the market. Severin Hacker CTO, Duolingo ” “ • Spoken language crucial for language learning • Accurate pronunciation matters • Faster iteration thanks to TTS • As good as natural human speech
- 33. ” “ Royal National Institute of Blind People creates and distributes accessible information in the form of synthesized content Amazon Polly delivers incredibly lifelike voices which captivate and engage our readers. John Worsfold Solutions Implementation Manager, RNIB • RNIB delivers largest library of audiobooks in the UK for nearly 2 million people with sight loss • Naturalness of generated speech is critical to captivate and engage readers • No restrictions on speech redistributions enables RNIB to create and distribute accessible information in a form of synthesized content RNIB provides the largest library in the UK for people with sight loss
- 34. Amazon ALEXA (It’s what’s inside Alexa) 3 Natural Language Understanding (NLU) & Automatic Speech Recognition (ASR) Powered By Deep Learning
- 35. The Advent Of Conversational Interactions 1st Gen: Machine-oriented interactions
- 36. The Advent Of Conversational Interactions 1st Gen: Machine-oriented interactions 2nd Gen: Control-oriented & translated
- 37. The Advent Of Conversational Interactions 1st Gen: Machine-oriented interactions 2nd Gen: Control-oriented & translated 3rd Gen: Intent-oriented
- 38. Amazon Lex: Speech Recognition & Natural Language Understanding Amazon Lex Automatic Speech Recognition Natural Language Understanding “What’s the weather forecast?” Weather Forecast
- 39. Amazon Lex: Speech Recognition & Natural Language Understanding Amazon Lex Automatic Speech Recognition Natural Language Understanding “What’s the weather forecast?” “It will be sunny and 25°C” Weather Forecast
- 40. Hotel Booking City New York City Check In Nov 30th Check Out Dec 2nd Hotel Booking City New York City Check In Check Out “Book a Hotel” Book Hotel NYC “Book a Hotel in NYC” Automatic Speech Recognition Hotel Booking New York City Natural Language Understanding Intent/Slot Model Utterances “Your hotel is booked for Nov 30th” Polly Confirmation: “Your hotel is booked for Nov 30th” a in “Can I go ahead with the booking?”
- 42. ” “ Finding missing persons: ~100,000 active missing persons cases in the U.S. at any given time ~60% are adults, ~40% are children • Motorola Solutions applies Amazon Rekognition, Amazon Polly and Amazon Lex • Image analytics and facial recognition can continually monitor for missing persons • Tools that understand natural language can enable officers to keep eyes up and hands free Motorola Solutions is using Amazon AI to help finding missing persons Motorola Solutions keeps utility workers connected and visible to each other with real-time voice and data communication across the smart grid.
- 43. I see… Amazon Rekognition Amazon Polly Camera Device Voice Synthesize Speech Detect Labels Detect Faces
- 45. Nikola Tesla, 1926 “When wireless is perfectly applied, the whole earth will be converted into a huge brain…”
- 46. Thank you! Danilo Poccia, Technical Evangelist @danilop
Hinweis der Redaktion
- All of these IoT devices are small devices with sensors that have little CPU and disk and make the cloud that much more important in supplementing their capabilities...
- All of these IoT devices are small devices with sensors that have little CPU and disk and make the cloud that much more important in supplementing their capabilities...
- Philips "At Philips we aim to empower people to take greater control of their health with connected digital health solutions,” says Jeroen Tas, CEO Healthcare Informatics, Solutions and Services, Philips. "Our HealthSuite digital platform already collects and manages the data of over seven million devices. Now that we have AWS IoT, we will greatly accelerate the pursuit of our vision by making it easy to ingest, process, and act upon data from heterogeneous devices in real time. Simply by changing business logic in the cloud, we can now instantly add new intelligence to existing MRI machines, disposable patient monitoring sensors and more. AWS IoT makes it possible for our products, and the care they provide, to grow smarter over time”
- Sonos: Video Case Study: https://www.youtube.com/watch?v=C9UVrbOMIZw
- All of these IoT devices are small devices with sensors that have little CPU and disk and make the cloud that much more important in supplementing their capabilities...
- Whatever is on the device when a customer starts using, that's the compute and options available to them unless they want to try to rewrite or program the device If you are regular dev and want to program on a device (set up triggers etc), it is hard w/o setting up an outage, so what we find is that you need better compute on the device itself. Really looking for same programming model as with AWS in devices. Instead of needing to write in new programming model. programming devices is hard, which makes updates hard Diverse across devices Different from what most developers use day to day
- Local Compute with Lambda AWS Greengrass includes support for AWS Lambda and AWS IoT Device Shadows. With Greengrass you can run AWS Lambda functions right on the device to execute code in near real-time. Secure Communications AWS Greengrass authenticates and encrypts device data at all points of connection, so that data is never exchanged between devices and the cloud without proven identity. Greengrass uses the same security and access management you are familiar with in AWS, with mutual device authentication and authorization, and secure connectivity to AWS IoT. Local data caching Greengrass also includes the functionality of AWS IoT Device Shadows, which create a persistent, virtual version, or “shadow,” of each device that includes the device’s latest state, so that applications or other devices can read messages and interact with the device. Local Messaging AWS Greengrass enables messaging between devices on a local network, so they can communicate with each other even when there is no connection to AWS. With Greengrass your devices can process messages and deliver them to another device or to AWS based on business rules you define.
- Local Compute with Lambda AWS Greengrass includes support for AWS Lambda and AWS IoT Device Shadows. With Greengrass you can run AWS Lambda functions right on the device to execute code in near real-time. Secure Communications AWS Greengrass authenticates and encrypts device data at all points of connection, so that data is never exchanged between devices and the cloud without proven identity. Greengrass uses the same security and access management you are familiar with in AWS, with mutual device authentication and authorization, and secure connectivity to AWS IoT. Local data caching Greengrass also includes the functionality of AWS IoT Device Shadows, which create a persistent, virtual version, or “shadow,” of each device that includes the device’s latest state, so that applications or other devices can read messages and interact with the device. Local Messaging AWS Greengrass enables messaging between devices on a local network, so they can communicate with each other even when there is no connection to AWS. With Greengrass your devices can process messages and deliver them to another device or to AWS based on business rules you define.
- Smart homes: lots of sensors and devices (light bulbs), which talk to a hub over wifi or bluetooth for orchestration and coordination. Hub talks to AWS as the canonical source for the rules and logic - but you don’t want your lights to stop working or your climate control to break if you lose internet connectivity. GG puts same orchestration and coordination abilities right on the smart hub. (This is how Philips Hue works). Agriculture: light weight sensors which need low latency orchestration and coordination - such as seed planters on a tractor which need to continually understand the planting depth based on land and weather conditions. Communicate over wired or wifi, bluetooth or using industrial wireless connectivity with a hub in the cab of the truck; don’t want the round trip latency in order to be able to analyze conditions and plant the seeds to the right depth, at the rate required for efficient crop growth. Manufacturing: where sensors provide a feedback loop to actuators to control a manufacturing process, where simple ad-hoc coordination is needed (no hub); devices can communicate with each other over an ad-hoc ‘mesh’ network (over wifi, bluetooth or using industrial wireless networking), and the exact same programming model, Lambda, can be used for coordination between the devices.
- All of these IoT devices are small devices with sensors that have little CPU and disk and make the cloud that much more important in supplementing their capabilities...
- Amazon has rich heritage of AI across the company. In the beginning of our retail business we made product recs, optimize pick paths at fulfilment center, xray products (see lyrics), think about alexa and echo devices. People wanted us to expose more and we are going to expose more. We perceive that people will want to build this into their apps. Introducing a family of services: amazon AI
- Intro: we've released several pieces already Transition: And, we see significant amounts of AI and ML workloads happening on AWS
- A new collection of tools called AMAZON AI, which brings the power of artificial intelligence, in all its flavors, to all developers. We’re announcing the first three today, focused on making deep learning models as easy as possible to use.
- The first is Rekognition. Lets take a look at how this works…
- * upload an image via API or SDK, Rekognition will analyze contents of image and tell you objects inside (person, woman, car, steering wheel)...makes it east to ad advanced search (e.g. give me women driving cars pics) * will detect faces and number of people so can generate thumbnails and crop faces well * can detect sentiment and details in faces (smiling, glasses) * face matching (good for security...e.g. Unlock laptops)
- Second is polly, which takes text, and uses deep learning to generate life like speech.
- The basics are pretty simple, but the service has deep functionality. You can send the service a simple it a simple string of text, and it will generate the life like voice in your choice of 47 different voices. But it’s not naive of the context of the text. For example, the text here - ‘WA’ and ‘degree F’, that would sound strange if it were spoken out loud, like I just had to. Instead, Polly will automatically expand the text strings ‘WA’ and ‘degree F’, to ‘Washington’ and ‘degrees fahrenheit’, to create more life like speech. The developer doesn’t have to do anything - just send the text, and get life like voice back.
- 19 min. DEEP LEARNING FOR G2P and PROSODY CONTOUR For phonemes – about use of Machine Learning For Contour – again – LSTM: We took audio Mention units adaptation to make sure that units match eacg other
- With Lex, any application running on the web, a mobile app, or a device, can send natural language - as both text or speech - to Lex using an API or SDK. Lex will apply ASR and NLU to the incoming message to understand the intent of the user, so to understand what the question is, and map that to a Lambda function which will process the information, and…
- Then form a response, which will be passed back to the user as either text, or will use Polly automatically to generate a voice response.
- Nikola Tesla: inventor of AC induction motor, early pioneer with radio and X-rays. Now - talk about learn and be curious - what better way than to turn the entire earth into a huge brain. That’s some think big right there.