Google Coral mPCIe and M.2 Cards for Sale, New Coral Dev Board Mini and Modules Coming in 2020

Google introduced Coral development board and USB accelerator with Google Edge TPU last year. The development board was comprised of a baseboard and Coral system-on-module with an NXP i.MX 8M quad-core Arm Cortex-A53 processor and the Edge TPU. Since then ASUS announced Tinker Edge T and CR1S-CM-A SBC based on the Coral module, and yesterday, I noticed Seeed Studio started selling mPCIe and M.2 AI accelerator card with Google Edge TPU, while today, Google announced upcoming Coral products for 2020. Coral Mini PCIe and M.2 Accelerators Coral Mini PCIe card specifications: Half-mini PCIe card with PCIe Gen2 x1 Supply voltage –  3.3VDC +/- 10 % Dimensions – 30.00 x 26.80 x 2.55 mm Weight – 3.6 g Temperature Range – Storage: -40 ~ 85°C; operating: -20 ~ 70°C Relative humidity – 0 ~ 100% (non-condensing) Op-shock – 100 G, 11ms (persistent); 1000 G, 0.5 ms (stress); 1000 G, 1.0 ms (stress) Op-vibe (random) – 0.5 Grms, 5 – 500 Hz …

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MediaPipe is an Open Source Perception Pipeline Framework Developed by Google

MediaPipe is an open-source perception pipeline framework introduced by Google, which helps to build multi-modal machine learning pipelines. A developer can build a prototype, without really getting into writing machine learning algorithms and models, by using existing components. This framework can be used for various vision & media processing applications (especially in VR) such as Object Detection, Face Detection, Hand Tacking, Multi-hand Tracking and Hair Segmentation. MediaPipe supports various hardware and operating system platforms such as Android, iOS & Linux by offering API’s in C++, Java, Objective-c, etc. And this framework also capable of utilizing GPU resources. MediaPipe Components The framework is comprised of three major components A framework for inference from the pipeline data Tools for evaluation And a collection of reusable inference and processing components It follows the approach of Graph-based frameworks in OpenCV and all processing happens with the context of the Graph. The Graph contains a collection of nodes and each node is implemented as a …

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Project Connected Home over IP (CHIP) Working Group is Backed by Google, Apple, Amazon, and the Zigbee Alliance

Amazon, Apple, Google, and Zigbee Alliance have partnered to create Project Connected Home over IP (CHIP) working group aiming to develop a royalty-free, Smart Home standard to increase compatibility among products, and with security at the forefront. The new standard will be separate from Zigbee 3.0 / Pro, and Zigbee Alliance board member companies such IKEA, Legrand, NXP Semiconductors, Resideo, Samsung SmartThings, Schneider Electric, Signify (formerly Philips Lighting), Silicon Labs, Somfy, and Wulian will also join the CHIP working group and contribute to the project. The standard specified by Project Connected Home over IP will rely on existing technology from the networking layer including TCP/UDP transport protocol, IPv6 network and various physical & media standards such as WiFi, Ethernet, Bluetooth LE, Cellular, 802.15.4 and others. Instead, it will define what happens at the application layer level with the following points of focus: End-to-end data security and privacy among in-home and mobile devices, and cloud services. A unified and standardized baseline …

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Google ADT-3 is a Developer-Focused TV Box for Android TV on Android 10

Google ADT-3 Android TV 10 Developer-Kit

Back in 2014, Google killed Google TV and announced Android TV, and as a result, introduced ADT-1, the first developer kit specifically designed for Android TV.  Since then ADT-2 was introduced in 2018 in an HDMI stick form factor, and now the company has announced the launch of Android TV on Android 10 together with ADT-3 devkit targetting Android TV app development for Android 10. The “developer kit” just looks like a standard TV box, although It’s really tiny and comes with what looks like a voice remote control. Google did not provide the full specifications, but ADT-3 is equipped with a quad-core Cortex A53 processor coupled with 2GB DDR3 memory, and supports 4Kp60 HDR video playback and output via an HDMI 2.1 output port. That probably means the box is powered by an Amlogic S905X2 processor since few other TV box SoCs combine 4x A53 cores with HDMI 2.1. The device is pre-certified, and will receive updates and security …

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Android 10 Released – What’s New?

Google released the first Android Q preview in March, and after several more preview, the company has finally released the latest version of the popular operating system which will simply be called Android 10, since Google dropped dessert names which previously led to confusion. What’s new in Android 10? Here’s a list of the new features that you can expect from Android 10: Privacy protection improvements – There’s more granular control over what apps can or cannot do in Android 10. Security improvements – Support for TLS 1.3 (up to 40% faster than TLS 1.2), and passive authentication methods such as face recognition Support for foldables and innovative new screens Sharing shortcuts – Let users jump directly into another app to share content. Settings Panels –  Floating UI invoked from an app to show system settings that users might need to adjust. Smart Reply in notifications – Contextual actions in notifications, such as smart replies for messages or opening a …

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Arm Techcon 2019 Schedule – Machine Learning, Security, Containers, and More

Arm Techcon 2019

Arm TechCon will take place on October 8-10, 2019 at San Jose Convention Center to showcase new solutions from Arm and third-parties, and the company has now published the agenda/schedule for the event. There are many sessions and even if you’re not going to happen it’s always useful to checkout what will be discussed to learn more about what’s going on currently and what will be the focus in the near future for Arm development. Several sessions normally occur at the same time, so as usual I’ll make my own virtual schedule with the ones I find most relevant. Tuesday, October 8  09:00 – 09:50 – Open Source ML is rapidly advancing. How can you benefit? by Markus Levy, Director of AI and Machine Learning Technologies, NXP Over the last two years and still continuing, machine learning applications have benefited tremendously from the growing number of open source frameworks, tools, and libraries to support edge inferencing. These include CMSIS-NN, ARM …

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Google Fuchsia Operating System Gets its own Developer Website

Fuchsia Documentation

Google has been developing Fuchsia open source operating system based on Zircon kernel for several years. It’s still unclear what’s the end goal. Will it replace Android or/and Chrome OS, ditching the Linux kernel for Zircon in the process? We don’t know, and Google claims its an experimental endeavor. Only the future will tell. We’ve had access to the source code since 2016,  but Google has now launched a dedicated developer website for Fuchsia: fuchsia.dev This is year 2019, and Google being a Western company it should not be surprising the first part of the documentation is a Code of Conduct, but there’s also plenty of technical documentation with a glossary, getting started guide, building instructions, an overview of the OS, code samples, and instructions to contribute either by testing or submitting changes to Gerrit. Fuchsia is strictly a 64-bit operating system at this stage with support for Arm64 and x86-64 ISA only. If you want to test drive Fuchsia …

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ASUS Tinker Edge T & CR1S-CM-A SBC to Feature Google Coral Edge TPU & NXP i.MX 8M Processor

ASUS CR1S-CM-A SBC

A few months ago, Google introduced its Coral development board and USB accelerator powered by their Edge TPU delivering up to 4 TOPS and optimized for Tensorflow Lite. ASUS and Google have now partnered to bring more solutions powered by Coral Edge TPU namely ASUS Tinker Edge T board for makers and hobbyists, CR1S-CM-A SBC for industrial projects, and even a full computer fitted with a Google Edge TPU PCIe card. ASUS Tinker Edge T ASUS Tinker Edge T preliminary specifications: SoC – NXP i.MX 8M quad-core Arm Cortex-A53 processor with Arm Cortex-M4F real-time core,  GC7000 Lite 3D GPU ML accelerator – Google Edge TPU co-processor System Memory – 1GB LPDDR4 RAM Storage – 8 GB eMMC flash Connectivity – Gigabit Ethernet port, Wi-Fi 2×2 MIMO (802.11b/g/n/ac 2.4/5GHz), and Bluetooth 4.1 Video Output – MIPI DSI connector, and HDMI output Camera I/F – 2x MIPI CSI 2 interfaces for stereoscopic camera applications USB – 2x USB 3.0 ports, 1x USB-C …

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