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November 7, 2019November 7, 2019 by Jean-Luc Aufranc (CNXSoft) - 6 Comments

NVIDIA Jetson Xavier NX SoM Delivers up to 21 TOPS for AI Workloads at the Edge

NVIDIA has just announced Jetson Xavier NX system-on-module, with the company claiming it is the “world’s smallest, most powerful AI supercomputer for robotic and embedded computing devices at the edge” with a 70x45mm “Jetson Nano” form factor, and delivering either up to 14 TOPS at 10 Watts or 21 TOPS at 15 Watts. The company expects the module to be used in small commercial robots, drones, intelligent high-resolution sensors for factory logistics and production lines, optical inspection, network video recorders, portable medical devices, and other industrial IoT systems. Jetson Xavier NX specifications: SoC – NVIDIA Xavier with 6-core NVIDIA Carmel ARM v8.2 64-bit CPU, 6MB L2 + 4MB L3 caches, and a 384-core NVIDIA Volta GPU with 48 Tensor Cores, 2x NVDLA deep learning accelerators delivering up to 21 TOPS at 15 Watts System Memory – 8 GB 128-bit LPDDR4x @ 51.2GB/s Storage – 16 GB eMMC 5.1 flash Video […]

November 7, 2019November 11, 2019 by Jean-Luc Aufranc (CNXSoft) - 145 Comments

Giveaway Week – Maixduino Sipeed M1 RISC-V AI Kit

For the fourth day of Giveaway Week, I’ll give out a kit comprised of Maixduino a RISC-V development board with an AI accelerator in Arduino form factor, a camera, and a 2.4″ color LCD. I tested the Maixduino kit with MicroPython, but it can also be programmed with the Arduino IDE, or Kendryte SDK. It basically allows you to run low-power AI workloads at the edge, i.e. without access to the cloud, such as face detection. To enter the draw simply leave a comment below. Other rules are as follows: Only one entry per contest. I will filter out entries with the same IP and/or email address. Contests are open for 48 hours starting at 10 am (Bangkok time) every day. Comments will be closed after 48 hours. If comments are open, the contest is still going on. Winners will be selected with random.org and announced in the comments section […]

November 6, 2019February 15, 2024 by Ayo Ayibiowu - 4 Comments

DepthAI Brings AI plus Depth to the Raspberry Pi (Crowdfunding)

Edge computing on the Raspberry PI has been a bit of ups and downs, especially with everyone gearing for AI in everything. The Raspberry Pi, on its own, isn’t really capable of any reliable AI applications. Typical object detection on the Raspberry Pi would get you something around 1 – 2 fps depending on the nature of your model and this because all those processing is done on the CPU. To address this poor performance of AI applications on the Raspberry Pi, AI Accelerators came to the rescue. The Intel Neural Compute Stick 2 is one such accelerator capable of somewhere around 8 – 15 fps depending on your application. The NCS2, which is based on the Myriad X VPU technology, offers so much more than the compute stick delivers, and this is something that the team behind DepthAI has exploited to create a powerful AI module for edge computing […]

November 5, 2019 by Stephen Vicinanza - No Comments

AuverCare is a Predictive AI 24/7 Monitor for Patients and Elderly

Information on the Internet for Monitoring Patients and Elderly If you are in the healthcare field or caring for an elderly or disabled person, you know all about trying to keep them safe. The internet is crowded with camera and audio monitors, wearable fall alert alarms, and the emergency services connected panic button. All these devices have one problem, they only work after there is a problem. What is Predictive AI? There has been a great deal of chatter since the 2016 announcement of a future predicting AI platform. The article reported on this platform was Predicting the Future – especially use cases such as falls by the elderly. With the advances in the field of AI and object recognition and behavior that is based on data gathered from a variety of sensors, it is not really a stretch to see a predictive healthcare monitor come onto the scene. Predictive […]

November 3, 2019 by Jean-Luc Aufranc (CNXSoft) - No Comments

BOOTPRINT X2 96Boards AIoT Development Kit Features Sunrise 2.0 AI Processor

Horizon Robotics BOOTPRINT X2 is an AIoT / AI computing development kit providing a complete reference solution from device to cloud integration. The board is powered by the company’s Sunrise 2.0 AI edge processor based on the second-generation BPU (“Brain Processing Unit”) architecture that delivers up to 4 TOPS at low power consumption and is said to follow 96Boards specification, although from the photo below they’ve taken some liberties with the option (e.g. added a Gigabit Ethernet port). The board has now launched yet, and we have limited information about BOOTPRINT X2 kit specifications: SoC – Horizon Sunrise 2.0 AI edge processor with 4 TOPS equivalent AI processing power (no mention of architecture) System Memory – 1GB LPDDR4 RAM Storage – 4GB eMMC flash, MicroSD card socket Connectivity – Gigabit Ethernet Camera I/F – Dual 1080p camera inputs for symmetric binocular camera, combination of infrared and visible light. Audio – […]

October 29, 2019 by Jean-Luc Aufranc (CNXSoft) - 13 Comments

Lixil AI-based Toilet Analyzes Shape & Size of Feces with Camera and LEDs

Earlier this year, we wrote about machine learning & image processing in embedded systems using pasta type classification as an example. Lixil Group, a Japanese company manufacturing housing equipment, is working on a concept using similar technology, but instead of classifying pasta, they implemented the technology into an AI-based toilet that checks the shape and size of feces of people living in elderly facilities. Lixil’s toilet was unveiled at the 46th International Home Care & Rehabilitation Exhibition (HCR 2019) in Tokyo at the end of last month. The system relies on a camera and two LED’s placed on the back of the seat, which turn on when the user sits on the seat. Once the job is done, images of the feces are taken automatically and classified into seven categories as specified by the Bristol stool chart. Classification happens within a few seconds, and results can be check by staff […]

October 24, 2019 by Jean-Luc Aufranc (CNXSoft) - 9 Comments

Orange Pi AI Stick Lite $20 Neural Compute Stick Ships with Free Training Tools

Shenzhen Xunlong Software launched Orange Pi AI Stick 2801 neural compute stick last year for $69. It was interesting as an alternative to Intel Neural Compute Stick. But once the documentation and SDK were released a few days later we discovered you could only run demos with the stick for that price, and the training tools would cost an extra $149. The excellent news is that the company has now launched an updated, yet similar Orange Pi AI Stick Lite for just $19.99, and best of all the PLAI training tools are now entirely free. Orange Pi AI Stick Lite specifications: ASIC – Gyrfalcon SPR2801S Lightspeeur series processor with 2-dimensional Matrix Processing Engine (MPE) with AI Processing in Memory (APiM) delivering up to 2.8TOPS @ 300mW, 5.6 TOPS @ 100 MHz (peak performance) Storage – eMMC 4.5 flash with 68 MB/s read, 84.69 MB/s write Host interface – USB 3.0/2.0 […]

October 23, 2019October 23, 2019 by Jean-Luc Aufranc (CNXSoft) - 1 Comment

Arm Introduces Ethos NPU Family, Mali-G57 GPU, and Mali-D37 Display Processor

Arm Ethos NPU: Ethos-M37, Ethos-N57 & Ethos-N77

Arm has just announced four new IP solutions with the most interesting being Ethos NPU (Neural Processing Unit) family with both Ethos-N57 and Ethos-N37 NPUs for mainstream devices, but the company also announced the new Arm Mali-G57, the first mainstream Valhall GPU, as well as Arm Mali-D37 DPU (Display Processing Unit) for full HD and 2K resolution. Arm Ethos NPU Family There are three members of the new Ethos family, and if you’ve never heard about Ethos-N77 previously, that’s because it was known as Arm ML processor. The three NPU’s cater to different AI workloads / price-point from 1 TOPS to 4 TOPS: Ethos-N37 Optimized for 1 TOP/s ML performance range 512 8×8 MAC/cycle 512KB internal memory Small footprint (<1mm2) For smart cameras, entry smartphones, DTV Ethos-N57 Optimized for 2 TOP/s ML performance range 1024 8×8 MAC/cycle 512KB internal memory For mainstream smartphones, smart home hubs Ethos-N77 Up to 4 […]