MediaTek Rich IoT SDK v20.0 was released at the beginning of the year together with the announcement of Pumpkin i500 SBC with very few details except it would be powered by MediaTek i500 octa-core Cortex-A73/A55 processor and designed to support computer vision and AI Edge Computing. Pumpkin i500 hardware evaluation kit was initially scheduled to launch in February 2020, but it took much longer, and Seeed Studio has only just listed the board for $299.00. We also now know the full specifications for Pumpkin i500 SBC: SoC – MediaTek i500 octa-core processor with four Arm Cortex-A73 cores at up to 2.0 GHz and four Cortex-A53 cores, an Arm Mali-G72 MP3 GPU, and dual-core Tensilica Vision P6 DSP/AI accelerator @ 525 MHz System Memory – 2GB LPDDR4 Storage – 16GB eMMC flash Display – 4-lane MIPI DSI connector Camera – Up to 25MP via MIPI CSI connector Video Decoding – 1080p60 H.264, H.265 / HEVC, MPEG-1/2/4 decoder, Encoding – 1080p30 H.264 […]
LG Electronics has designed LG8111 AI SoC for on-device AI inference and introduced the Eris Reference Board based on the processor. The chip supports hardware processing in artificial intelligence functions such as video, voice, and control intelligence. LG8111 AI development board is capable of implementing neural networks for deep learning specific algorithms due to its integrated “LG-Specific AI Processor.” Also, the low power and the low latency feature of the chip enhances its self-learning capacity. This enables the products with LG8111 AI chip to implement “On-Device AI.” Components and Features of the LG8111 AI SoC LG Neural engine, the AI accelerator has an extensive architecture for “On-Device” Inference/Leaning with its support on TensorFlow, TensorFlow Lite, and Caffe. The CPU of the board comes with four Arm Cortex A53 cores clocked at 1.0 GHz, with an L1 cache size of 32KB and an L2 cache size of 1MB. The CPU also enables NEON, FPU, and Cryptography extension. The camera engine has […]
Himax WE-I Plus EVB is a low-power AI development board focused on machine learning and deep learning applications with its support for the TensorFlow Lite framework for Microcontrollers. It consists of majorly two significant components. First, HX6537-A ASIC is an ultra-low-power microcontroller designed for battery-powered TinyML applications. Second, HM0360 VGA mono camera with ultra-low power and CMOS image sensing features for CV(Computer Vision) based applications like object classification and recognition. The All in One AI Development Board The Development Board consists of HX6537-A ASIC, with built-in ARC EM9D DSP working at 400MHz frequency. It contains internal 2MB ultra-low leakage SRAMs for system and program usage. It also contains two LEDs to display classification results. Connections with external sensors/devices can be established using I2C and GPIOs interface present in its expansion header. “The all-in-one WE-I Plus EVB includes an AI processor, HM0360 AoS VGA camera, 2 microphones, and a 3-axis accelerometer to perform vision, voice, and vibration detection and recognition. It […]
In the past, Bluetooth, Wi-Fi, 3G, 4G with onboard sensors and GPS gave a huge start to the partial or conditional automation of the vehicles. In today’s era of 4G/5G C-V2X (Cellular vehicle-to-everything) with onboard compute and sensors have pushed the connectivity evolution in the automotive industry. Work has increased on high-automation and fully autonomous vehicles. This is all possible due to wireless communication which is 5G. 5G brings high bandwidth, ultra-low latency, and high reliability to the board. With these promises, it becomes very evident that these technologies, specifically with 5G that can be leveraged in vehicles. The technology is not just to connect vehicles, but also tries to see if a vehicle can connect to a network to get some information from the cloud servers. For the use case of vehicles platooning, we can expect a latency of 10 ms with 99.99% reliability and a high data rate of up to 65 Mbps to ensure that the vehicles […]
Last week, Mythic announced a breakthrough with compute-in-memory technology based on a 40 nm process with what the company claims to be the industry’s first Analog Matrix Processor. The M1108 AMP AI accelerator chip targets high-end edge AI applications including smart home, AR/VR, drones, and is said to set a benchmark in the industry for high performance and low power in a single cost-effective device, also available in M.2 and PCIe form factors. The M1108 comes with an array of flash cells, ADCs, a 32-bit RISC-V nano-processor, a SIMD vector engine, SRAM, and a high-throughput Network-on-Chip (NOC) router. With 108 AMP tiles, the M1108 provides up to 35 Trillion-Operations-per-Second (TOPS) enabling ResNet-50 at up to 870 fps. This enables a power-efficient execution of complex AI models such as ResNet-50, YOLOv3, and OpenPose Body25. The industry leader NVIDIA also has a similar AI accelerator chip NVIDIA Xavier AGX which delivers up to 32 TOPS. A wide variety of host processors are […]
Arm introduced their very first microNPU (Micro Neural Processing Unit) for microcontrollers at the beginning of the year with Arm Ethos-U55 designed for Cortex-M microcontrollers such as Cortex-M55, and delivering 64 to 512 GOPS of AI inference performance or up to a 480x increase in ML performance over Cortex-M CPU inference. The company has now unveiled an update with Arm Ethos-U65 microNPU that maintains the efficiency of Ethos-U55 but enables neural network acceleration in higher performance embedded devices powered by Arm Cortex-A and Arm Neoverse SoCs. Arm Ethos-U65 delivers up to 1 TOPS, and as seen in the diagram enables features that can not be done with Ethos-U55 including object classification and real-time classification. Compared to Ethos-N78 NPU, the new microNPU offers less AI performance, but a significantly higher efficiency although AFAIK no quantified by Arm. The company says the development workflow remains the same with the use of the TensorFlow Lite Micro (TFLmicro) runtime that runs on a Cortex-M […]
Google Coral SBC was the first development board with Google Edge TPU. The AI accelerator was combined with an NXP i.MX 8M quad-core Arm Cortex-A53 processor and 1GB RAM to provide an all-in-all AI edge computing platform. It launched for $175, and now still retails for $160 which may not be affordable to students and hobbyists. Google announced a new model called Coral Dev Board Mini last January, and the good news is that the board is now available for pre-order for just under $100 on Seeed Studio with shipping scheduled to start by the end of the month. Coral Dev Board Mini specifications haven’t changed much since the original announcement, but we know a few more details: SoC – MediaTek MT8167S quad-core Arm Cortex-A35 processor @ 1.3 GHz with Imagination PowerVR GE8300 GPU AI/ML accelerator – Google Edge TPU coprocessor with up to 4 TOPS as part of Coral Accelerator Module System Memory – 2GB LPDDR3 RAM Storage – […]
Earlier this year, we covered some video analytics solutions based on AAEON UP Xtreme Edge embedded computer combining an Intel Whiskey Lake processor with Intel Movidius Myriad X AI accelerator modules, as well as video management & analytics software solutions from Milestones & SAIMOS, or aotu.ai BrainFrame. iWave Systems has now introduced a similar solution with Corazon-AI gateway capable of handling up to 8 IP cameras in real-time, but instead of relying on AI accelerators, the company leverages Xilinx Zynq Ultrascale+ Arm Cortex-A53/R5 FPGA MPSoC for AI inference. Corazon-AI gateway specifications: SoC – Xilinz Zynq Ultrascale+ ZU2, ZU3, ZU4 or ZU5 MPSoC Processing System (PS) Quad/Dual Arm Cortex-A53 @ 1.5GHz, dual Cortex-R5 @ 600MHz Arm Mali-400MP2 GPU @ 677MHz H.264/H.265 Video Encoder/Decoder Programming Logic (PL) Up to 256K Logic cells PL GTH Transceivers x 4 @ 12.5 Gbps System Memory 64bit, 2GB DDR4 with ECC for PS (upgradable) 32bit, 1GB DDR4 for PL (upgradable) Storage – 8GB eMMC Flash (upgradable), […]
Privacy & Cookies Policy
Necessary cookies are absolutely essential for the website to function properly. This category only includes cookies that ensures basic functionalities and security features of the website. These cookies do not store any personal information.
Any cookies that may not be particularly necessary for the website to function and is used specifically to collect user personal data via analytics, ads, other embedded contents are termed as non-necessary cookies. It is mandatory to procure user consent prior to running these cookies on your website.