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Using a trained model on your mobile device
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Lars Gregori
Project Malmo from Microsoft is a platform to use Minecraft as a AI testing ground. It's not about playing the game, it's about using Minecraft as an experimental platform for AI. In my talk I'll show how to solve individual problems with reinforcement learning, Minecraft, and project Malmo.
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You are likely benefitting from The Internet of Things (IoT) today, whether or not you’re familiar with the term. If your phone automatically connects to your car radio, or if you have a smartwatch counting your steps, congratulations! You have adopted one small piece of a very large IoT pie, even if you haven't adopted the name yet. IoT may sound like a business buzzword, but in reality, it’s a real technological revolution that will impact everything we do. It's the next IT Tsunami of new possibility that is destined to change the face of technology, as we know it. IoT is the interconnectivity between things using wireless communication technology (each with their own unique identifiers) to connect objects, locations, animals, or people to the Internet, thus allowing for the direct transmission of and seamless sharing of data. IoT represents a massive wave of technical innovation. Highly valuable companies will be built and new ecosystems will emerge from bridging the offline world with the online into one gigantic new network. Our limited understanding of the possibilities hinders our ability to see future applications for any new technology. Mainstream adoption of desktop computers and the Internet didn’t take hold until they became affordable and usable. When that occurred, fantastic and creative new innovation ensued. We are on the cusp of that tipping point with the Internet of Things. IoT matters because it will create new industries, new companies, new jobs, and new economic growth. It will transform existing segments of our economy: retail, farming, industrial, logistics, cities, and the environment. It will turn your smartphone into the command center for the both digital and physical objects in your life. You will live and work smarter, not harder – and what we are seeing now is only the tip of the iceberg.
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TensorFlow Serving brings machine learning models in production with Bring Your Own Model (BYOM). We are all able to create a model, to find some data and train the model. But how do you host a model? In my presentation I will give an overview and demo of TensorFlow Serving. In addition, I will show in an example how to train and host a model. But more important, I will show how you can access the model and the possibilities.
BYOM - Bring Your Own Model
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Lars Gregori
TensorFlow has already made it possible to use trained machine learning models on smartphones. TensorFlow Lite goes one step further and run TensorFlow models on a Raspberry Pi. uTensor even puts AI on a microcontroller (MCU). They are small and cheap, but they are also energy efficient, slow and have little RAM, which doesn’t make it any easier. In my presentation I will take a simple machine learning model on TensorFlow and show why it will NOT work with uTensor. But don’t worry, I will also show a working example. I will also go a little bit deeper into TensorFlow operators and you will see also some C/C++ code.
uTensor - embedded devices and machine learning models
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Lars Gregori
an overview of SAP Leonardo Machine Learning for the SAP Stammtisch Meetup (out of my book http://sappress.de/4795 )
SAP Leonardo Machine Learning
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Minecraft and reinforcement learning
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Lars Gregori
Nowadays, mobile devices have enough computing power to run pre-trained models on them. This results in an optimal use of the hardware and an increase in speed, because the data are not sent over the Internet, which also means more privacy. In my presentation I will show different ways to integrate machine learning models into an iOS and Android application. The participants will learn how to integrate a pre-training model into an iOS and Android application with CoreML and Tensorflow Lite, and how to re-train a model for own pictures and use it instead of the pre-trained model. All examples are shown in a small demo. https://www.mcubed.london/sessions/machine-learning-models-mobile-devices/
Machine Learning Models on Mobile Devices
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Lars Gregori
Minecraft and Reinforcement Learning Project Malmo was initiated by Microsoft Research as a platform to use Minecraft as an AI testing ground. It's not about playing the game, it's about using Minecraft as an experimental AI platform. In my talk I'll take a look into reinforcement learning and how to solve individual problems with (deep) reinforcement learning, Minecraft, and project Malmo.
Minecraft and Reinforcement Learning
Minecraft and Reinforcement Learning
Lars Gregori
IoT protocols or Pay per Use (but my washing machine couldn't pay) "Pay per Use is 'the next big' business model where you only pay for a thing when you use it, which could be a digital or a physical thing. Mostly an Internet connection is required for the payment, but what happens when e.g., your washing machine is too far away from your Wi-Fi connection? In my presentation I'll talk about "our" Revenue Cloud. The main part will be about different IoT protocols as alternative to a Wi-Fi connection." https://www.meetup.com/IoTMunich/events/249742137/
IoT protocolls - smart washing machine
IoT protocolls - smart washing machine
Lars Gregori
Das Projekt Malmo ist eine von Microsoft initiierte Plattform, um Minecraft als AI-Testumgebung zu verwenden. Dabei geht es nicht um Minecraft als Spiel, sondern vielmehr um eine experimentelle AI-Plattform.
[DE] AI und Minecraft
[DE] AI und Minecraft
Lars Gregori
Project Malmo was initiated by Microsoft Research as a platform to use Minecraft as an AI testing ground. It's not about playing the game, it's about using Minecraft as an experimental AI platform. In the talk, Lars is going to take a look into reinforcement learning and how to solve individual problems with (deep) reinforcement learning, Minecraft, and project Malmo. Hacking Machine Learning Meetup: https://www.meetup.com/Hacking-Machine-Learning/events/248225473/
Minecraft and Reinforcement Learning
Minecraft and Reinforcement Learning
Lars Gregori
Pay per use ist ein Geschäftsmodell, bei dem für die tatsächliche Nutzung eines Gegenstands bezahlt wird. Dabei kann es sich um einen digitalen oder physischen Gestand handeln, der meist eine Internetverbindung für die Abrechnung benötigt. Was passiert aber, wenn zum Beispiel die Waschmaschine im Keller das Heimnetzwerk nicht erreicht? In diesem Vortrag zeige ich verschiedene Protokolle, die alternativ zu einer WiFi-Verbindung Verwendung finden können.
[DE] IoT Protokolle
[DE] IoT Protokolle
Lars Gregori
Apple announced at WWDC17 with iOS 11 CoreML. This allows you to integrate trained machine learning models into your iOS app. It has a minimizes memory footprint and power consumption and is optimized for on-device performance. In my talk I'll show how to train a very simple model and how to integrate it into a mobile app. Another demo will use InceptionV3 as pre-trained model and ARKit for augmented reality visualization.
Using a trained model on your mobile device
Using a trained model on your mobile device
Lars Gregori
Apple announced at WWDC17 with iOS 11 CoreML. This allows you to integrate trained machine learning models into your iOS app. It has a minimizes memory footprint and power consumption and is optimized for on-device performance. In my talk I'll show how to train a very simple model and how to integrate it into a mobile app. Another demo will use InceptionV3 as pre-trained model and ARKit for augmented reality visualization.
Using a trained model on your mobile device
Using a trained model on your mobile device
Lars Gregori
Project Malmo from Microsoft is a platform to use Minecraft as a AI testing ground. It's not about playing the game, it's about using Minecraft as an experimental platform for AI. In my talk I'll show how to solve individual problems with reinforcement learning, Minecraft, and project Malmo.
AI and Minecraft
AI and Minecraft
Lars Gregori
IoT Boards (e.g. Arduino, Raspberry Pi, ESP8266, ...) for prototyping with price tags, technical information and comparison between MCU, MPU and SoC (System on a Chip)
[German] Boards für das IoT-Prototyping
[German] Boards für das IoT-Prototyping
Lars Gregori
Node-RED allows to connect and configure IoT devices, APIs and Microservices. (Slides from my Internet of Thing Conference talk.)
IoT, APIs und Microservices - alles unter Node-RED
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Lars Gregori
With Web Bluetooth API your browser can connect to Bluetooth devices.
Web Bluetooth - Next Generation Bluetooth?
Web Bluetooth - Next Generation Bluetooth?
Lars Gregori
Slides for my Embedded Rust talk at #Devoxx 2016. Rust is a systems programming language that runs blazingly fast, prevents segfaults and runs on embedded IoT devices.
Embedded Rust – Rust on IoT devices
Embedded Rust – Rust on IoT devices
Lars Gregori
Rust is a systems programming language that runs blazingly fast, prevents segfaults and runs on embedded IoT devices.
Embedded Rust on IoT devices
Embedded Rust on IoT devices
Lars Gregori
Slides (in German) from my Building IoT Talk "IoT mit Rust programmieren" which (tries) to answer the question: Can Rust be a solution for embedded IoT devices (instead of C/C++), which are: connected to the internet developed in a short time storing personal data secure more intelligence inexpensive
IoT mit Rust programmieren
IoT mit Rust programmieren
Lars Gregori
slides from my Building IoT Talk (Boards für das IoT-Prototyping) about IoT-Prototyping boards which we use at #hybrislabs
Boards for the IoT-Prototyping
Boards for the IoT-Prototyping
Lars Gregori
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BYOM - Bring Your Own Model
BYOM - Bring Your Own Model
uTensor - embedded devices and machine learning models
uTensor - embedded devices and machine learning models
SAP Leonardo Machine Learning
SAP Leonardo Machine Learning
Minecraft and reinforcement learning
Minecraft and reinforcement learning
Machine Learning Models on Mobile Devices
Machine Learning Models on Mobile Devices
Minecraft and Reinforcement Learning
Minecraft and Reinforcement Learning
IoT protocolls - smart washing machine
IoT protocolls - smart washing machine
[DE] AI und Minecraft
[DE] AI und Minecraft
Minecraft and Reinforcement Learning
Minecraft and Reinforcement Learning
[DE] IoT Protokolle
[DE] IoT Protokolle
Using a trained model on your mobile device
Using a trained model on your mobile device
Using a trained model on your mobile device
Using a trained model on your mobile device
AI and Minecraft
AI and Minecraft
[German] Boards für das IoT-Prototyping
[German] Boards für das IoT-Prototyping
IoT, APIs und Microservices - alles unter Node-RED
IoT, APIs und Microservices - alles unter Node-RED
Web Bluetooth - Next Generation Bluetooth?
Web Bluetooth - Next Generation Bluetooth?
Embedded Rust – Rust on IoT devices
Embedded Rust – Rust on IoT devices
Embedded Rust on IoT devices
Embedded Rust on IoT devices
IoT mit Rust programmieren
IoT mit Rust programmieren
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Boards for the IoT-Prototyping
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IoT Chess Lars Gregori,
@choas mnug, 10.12.2015
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Agenda History Tools Demo
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4.
Tools • mosca • mqtt
(eclipse paho) • uci • stockfish • node-red • chessboardjs • simple-server
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Thank you Lars Gregori @choas
6.
Links • https://www.npmjs.com/package/mosca • https://www.eclipse.org/paho/clients/js/ •
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Download now