GAPUINO GAP8 is a $229 RISC-V MCU Developer Kit for A.I. Applications

GAPuino Board

GreenWaves GAP8 is a low power RISC-V “MCU class” processor with eight compute cores optimized for artificial intelligence applications, and its main selling point is the ability to do tasks like computer vision or audio processing at very low power, even good enough to run on batteries. When we first covered GAP8 RISC-V processor at the beginning of the year, the company also mentioned a development kit comprised of GAPDUINO Arduino compatible board, a sensor board, and a QVGA camera module to experiment with the solution.  The board and development kit are now easier to purchase as the devkit is sold on SeeedStudio for $229. GAPuino board specifications: SoC – GAP8 IoT Application Processor with 8x RISC-V  compute cores, 1x RISC-V fabric controller core delivering up to 200 MOPS at 1mW and  >8 GOPS at a few tens of mW Memory / Storage –  HyperBus combo DRAM/Flash with 512 Mbit Flash + 64 Mbit DRAM; 256 Mbit Quad SPI flash …

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Firefly Baidu Face Recognition Kit Comes with Monocular, Binocular, or Structured Light Camera

Baidu Face Recognition Kit

Firefly AIO-3399J industrial board comprised of a Rockchip RK3399 SoM and a baseboard offering plenty of I/O & connectivity options has been bundled with various  other accessories including a 10.1″ touchscreen display, and cameras to create a development platform for Baidu AI offline (aka “at the edge”) face recognition technology. The development kit is available in different variants with either a monocular camera, a binocular camera, or a structured-light camera. There’s also a deluxe kit with WiFi and a stand. Baidu Face Recognition Kit key specifications: SoC – Rockchip RK3399 hexa-core big.LITTLE processor with dual core ARM Cortex A72 up to 2.0 GHz and quad core Cortex A53 processor, ARM Mali-T860 MP4 GPU with OpenGL 1.1 to 3.1 support, OpenVG1.1, OpenCL and DX 11 support System Memory – 2GB DDR3 RAM Storage – 16GB eMMC 5.1 flash, micro SD card slot Display – 10.1″ 1280×800 capacitive touch display Connectivity – Gigabit Ethernet, Dual band WiFi, Bluetooth 4.1 LE, and mPCIe …

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Imagination Unveils PowerVR AX2185 and AX2145 Neural Network Accelerators (NNA)

PowerVR AX2185

Imagination Technologies introduced PowerVR Series2NX neural network accelerator (NNA) last year. At the time, the company claimed the NNA would deliver  twice the performance at half the bandwidth over existing competing solutions, and that it was the first dedicated hardware solution with flexible bit-depth support from 16-bit down to 4-bit. What they did not announce last September were any specific parts. But they’ve just done that today with PowerVR AX2185 and AX2145 NNAs “designed to enable high-performance computation of neural networks at very low power consumption in minimal silicon area”. PowerVR AX2185 PowerVR AX2185 is said to be the highest performing neural network accelerator per mm2 in the market with eight full-width compute engines delivering up to 4.1 TOPS (Tera Operations Per Second), or 2,048 MACs/clock. AX2185 NNA can deliver 3.5 times the performance compared to a desktop GPU. The NNA is best suited for high-end smartphones, smart surveillance and automotive markets. PowerVR AX2145 PowerVR AX2145 is a lower cost …

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NVIDIA Introduces Jetson Xavier Devkit and Isaac Robotics Software

NVIDIA Jetson Xavier

NVIDIA Xavier was first unveiled in September 2016 as an artificial intelligence SoC with eight NVIDIA Custom 64-bit Arm cores, a 512-core Volta GPU,  8K video encoding and decoding, and a computer vision accelerator (CVA) now called NVDLA (NVIDIA Deep Learning Accelerator). Earlier this year, the company announced Xavier was sampling,  and DRIVE IX & DRIVE AR SDKs for the automotive market. On the eve of Computer 2018, NVIDIA has introduced Jetson Xavier development kit, as well as Isaac robotics software for autonomous machines. Jetson Xavier key specifications: SoC – NVIDIA Xavier with 8-core ARMv8.2 64-bit CPU, 8MB L2 + 4MB L3 512-core Volta GPU with Tensor Cores 2x NVDLA engines for deep learning 7-way VLIW Processor for vision acceleration VPU with dual 4Kp60 video decoding and encoding System Memory – 16GB 256-bit LPDDR4x | 137 GB/s Storage – 32GB eMMC 5.1 flash Display – 3x eDP/DP/HDMI at 4Kp60 | HDMI 2.0, DP HBR3 Camera 16x CSI-2 Lanes (40 Gbps …

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Android 8.1 Firmware and SDK Released for Orange Pi 4G-IoT Board

Orange-Pi-4G-IoT-Android-8.1

When Orange Pi 4G-IoT board launched a few months ago, it shipped with a not so recent Android 6.0 operating system. But the good news is that Shenzhen Xunlong Software has now released Android 8.1 firmware for their Mediatek MT6737M quad core Cortex A53 LTE Cat 4 board, as well as the corresponding SDK. This makes it the cheapest Android 8.1 board with LTE connectivity available on the market so far as it goes for just under $50. The SDK is a large tarball (22.6 GB) split into 11 smaller files. It’s hosted on MEGA so download is fairly fast, but due to the size I had to install MEGA Sync software in order to download it easily. Once the download is complete, it’s not recognized in Nautilus, but you can extract the SDK as follows in a terminal: This will take a while and extract over a million files for a total of 64.8 GB. We can now have …

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Sens’it Discovery is a Sigfox IoT Solution with 6 Sensors

Sigfox has just launched Sens’it Discovery, which they describe as a “end-to-end IoT solution, which aims to accelerate the adoption of the IoT (Internet of things) among business and technical professionals”. The solution is comprised for Sens’it 3 device with 6 sensors, sensit.io application, and Sigfox connectivity. Sens’it 3 hardware specifications: MCU – STM32 micro‑controller  Connectivity TI CC1125 radio transceiver Sigfox Ready class 0U Frequencies – 868 to 869.7 MHz, 902 to 908 MHz, or 923.2 MHz (TX) / 922.2 MHz (RX), or 920 to 925 MHz depending on region Transmit Power emission – 14 dBm ERP (RC1), 22 dBm ERP (RC2), 10 dBm ERP (RC3), 22 dBm ERP (RC4) Sensors Thermometer (HTS221) – -40 to 120°C / Accuracy ± 0.5°C Humidity (HTS221) –  0 to 100 / Accuracy ± 3.5% rH (20 to +80% rH) Accelerometer (FXOS8700) –  ±2, 4, 8 g / Accuracy 0.244, 0.488, 0.976 mg Magnetometer (FXOS8700) –  ±1200 μT / Sensitivity 0.1 μT/LSB Light (LTR329) –  …

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Nordic Semiconductor nRF52840 Multiprotocol SoC Adds Support for Zigbee 3.0

Nordic Semiconductor nRF52840 was introduced in late 2016 as one of the first Bluetooth 5 ready SoC, and it’s the only  part from Nordic that fully supports Bluetooth 5 longer range. But the chip is actually a multiprotocol SoC and beside Bluetooth, 802.15.4, Ant, Thread and 2.4 GHz proprietary are also supported.  The company has now announced one more wireless protocol working on nRF52840: Zigbee 3.0. The company has released the first engineering release for Zigbee on nRF52840, but the production grade Zigbee 3.0 certified release is planed for H2 2018. The new protocol will be enabled in the S410 v6.0 SoftDevice release. Bluetooth and  Zigbee can run concurrently meaning for example you could create an nRF52840 gateway to control Zigbee smart lights from a smartphone connected over Bluetooth 5. The SDK includes examples for concurrent operation of Zigbee and Bluetooth 5 for a smart light bulb and switch. The company further explains raw data throughput rates of 250kbs can …

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Qualcomm QCS603 / QCS605 “IoT” SoCs are Designed for AI and Computer Vision Applications

Qualcommn has unveiled the “Qualcomm Vision Intelligence Platform”, which aims at IoT devices with camera leveraging artificial intelligence and computer vision. The first SoCs part of the platform are QCS605 and QCS603 manufactured with a 10nm process, and equipped with an “advanced image signal processor” and the Qualcomm Artificial Intelligence (AI) Engine, as well Arm CPU cluster, Adreno GPU, and Hexagon DSP. QCS603 & QCS605 specifications: CPU QCS603 – 2x 1.6GHz Qualcomm Kryo 300 Gold cores, 6x 1.7GHz Qualcomm Kryo 300 Silver cores QCS605 – 2x 2.5GHz Qualcomm Kryo 300 Gold cores, 6x 1.7GHz Qualcomm Kryo 300 Silver cores Qualcomm Artificial Intelligence Engine DSP Qualcomm Hexagon 685 Vector Processor 2x Qualcomm Hexagon Vector eXtensions (HVX) GPU – Qualcomm Adreno 615 with OpenGL ES 3.2, Vulkan, OpenCL support Neural Processing – Qualcomm Snapdragon Neural Processing Engine programming interface with support for Tensorflow, Caffe/Caffe2, ONNE, Android NN; 2.1 TOPS @ 1w Memory I/F – 16-bit LPDDR4x @ up to 1866MHz Connectivity WiFi …

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