Azure IoT Edge now features support for running natively on the Kubernetes orchestrator. This video goes into how the integration works and caps off with a demo showing what the experience is like for deploying a workload on an on-premise Kubernetes cluster. Give this a spin yourself on your own Kubernetes cluster (or create one using Azure Kubernetes Service) using the Kubernetes on Edge How-to guide. Azure Kubernetes
In this video, learn about the recently announced IoT Plug and Play, which is based on an open modeling language that allows IoT devices to declare their capabilities. That declaration, which is called a Device Capability Model, is then presented when IoT devices connect to cloud solutions like Azure IoT Central and Partner Solutions which can then automatically understand the device and start interacting with it– all without writing any code.
For $35 you can get a quad core 1.44Ghz x86 processor on a single board. This is going to power a lot of IoT solutions.
BBC Click takes a loot at 5G and how it will impact mobile networks and IoT.
Microsoft Build 2019 is next week, and in this episode of the IoT Show see what goes on inside Azure IoT’s building on the Microsoft Campus and meet some of the speakers who are preparing awesome IoT content for you.
Find the full list of IoT content and sessions at build: https://aka.ms/IoTatMSBuild2019
Here’s a great video on how to work with Azure IoT Hub, Device Provisioning Service, Azure Stream Analytics and IoT Edge
In this episode of BBC Click, they explore a new art installation in Paris, the Pope weighs in on the ethics of Robotics and AI.
Azure Stream Analytics is a PaaS cloud offering on Microsoft Azure to help customers analyze IoT telemetry data in real-time. Stream Analytics now has embedded ML models for Anomaly Detection, which can be invoked with simple function calls. Learn how you can leverage this powerful feature set for your scenarios.
Learn more : https://docs.microsoft.com/en-us/azure/stream-analytics/stream-analytics-machine-learning-anomaly-detection
Create a Free Account (Azure): https://aka.ms/aft-iot
If you’re in the Maker community and have been wanting to get into AI, the release of the Jetson Nano may be just the device you’ve been waiting for.
Here’s a great introduction to the world of AI for Makers.
For Humans identification of any object by just seeing towards it done within few second, it’s really easy for them, but when we concern about the machine to identify the object, it is the really complex thing until Hinton and Alex Krizhevsky won the champion of ImageNet in 2012. Then Neural Network dominated Vision field, especially the problem of classification and segmentation, and the convolutional neural network is one of the most prominent approaches who won numerous competitions in recent years. It has outstanding results in image recognition. Nvidia has built a lot of Vision Demo for Jetson Nano, and we have tested two of them as classification and face detection: