Use containerized device tool chain in Azure IoT Device Workbench to simplify device tool chain acquisition challenge.
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It’s April the Fool but this is real. We made a huge performance improvement by reduing the extension load-up time 10 times faster. Here are what’s new for Azure IoT Device Workbench 0.2.6:
New sample: “IoT Devkit Dictionary”. Using Microsoft Cognitive Service in IoT devices is always an interesting topic.
Together with the new Azure IoT Tools for VS Code extension pack, we also overhauled the experience of Azure IoT Device Workbench. And there is another exciting sample contributed by Chris Lovett (Github) from Microsoft Research about running Embedded Learning Library (ELL) on MXChip IoT DevKit to achieve the keyword spotting locally.
In April this year, we released our first public preview of Azure IoT Workbench in Visual Studio Code, an IoT development environment aims to make it easy to code, build, deploy and debug your IoT project for MXChip IoT DevKit. From this one DevKit,
It’s been around 4 months since we release our official hardware and SDK as v1.0 last September right on Ignite 2017. In that event, the MXChip IoT DevKit was used on a couple of Azure IoT break-out and keynote sessions for demonstrations and together with announcement with new services released such as IoT Hub Device Provisioning Service.
DevKit is available for pre-ordering
During the past two months, we have been keeping sending out preview IoT DevKit for evaluation to a selective group of requestors. And we see increasing demand for the kits from developers around the world, from Canada to Brazil,