artificial intelligence (AI) News - Page 96 of 121 - CNX Software

November 28, 2019 by Jean-Luc Aufranc (CNXSoft) - No Comments

Hacarus Embedded AI Computing Kit Leverages Sparse Modeling Technology

Hacarus AI Computing Kit Sparse Modeling Technology

AI training often requires thousands of samples to become accurate, and it can be costly and time-consuming, for example, if you want to train a model to detect manufacturing defects you’d need to provide images with both defective samples and good samples. Japanese AI experts at Hacarus have been working on a solution called Sparse Modeling which requires about 50 samples or even less for training, and worked with Congatec to provides an embedded AI computing kit leveraging the technology. Sparse Modeling Technology Hacarus does not go into great detail but explains Sparse Modeling technology is using a data modeling approach that focuses on identifying unique characteristics, in a way that humans recognize friends and family without having to look at everything from feet to head. That means algorithms based on Sparse Modeling do not need as much data as traditional AI solutions, leading to much smaller AI footprint suitable […]

November 27, 2019 by Jean-Luc Aufranc (CNXSoft) - 2 Comments

AAEON BOXER-8220AI Embedded Box PC Features NVIDIA Jetson Nano, 5 Gigabit Ethernet Ports

AAEON has launched several AI Boxer-8000 series embedded box PCs based on Intel processors plus AI accelerator, or NVIDIA Jetson TX2. The company has now introduced a new model – BOXER-8220AI – based on NVIDIA Jetson Nano module, and equipped with five Gigabit Ethernet ports. AAEON BOXER-8220AI specifications: SoM (CPU/Memory/Storage) – NVIDIA Jetson Nano with quad-core Arm Cortex-A57 MPCore processor @ 1.43 GHz, 128-core Maxwell GPU. 4GB LPDDR4, 16GB eMMC flash or MicroSD card Video Output – HDMI 2.0 Connectivity – 5x Gigabit Ethernet ports USB – 4x USB 3.0 ports, 1x Micro USB to flash the OS Serial – 2x RS-232 Misc – Power button, recovery button, power LED Power Supply – 10-24V DC via 2-pin terminal block Dimensions – 154 x 101 x 30 mm Weight – 1 kg Temperature Range – Operating: -20°C ~ 60°C, according to IEC60068-2 with 0.5 m/s AirFlow; storage: -45°C ~ 80°C Storage […]

November 22, 2019November 23, 2019 by Jean-Luc Aufranc (CNXSoft) - 3 Comments

Zidoo M9 is a Rockchip RK3399 TV Box/Mini PC/SBC with Android 7.1 + SDK

Zidoo has launched several TV boxes running Android over the years, some of which we reviewed such as Zidoo X9 (2015), or Zidoo H6 Pro. They also have experience launched dual-OS systems with Android and OpenWrt running simultaneously for multimedia and router functions respectively through their Zidoo X9S media center. The company has now contacted CNX Software to review their latest model. Zidoo M9 is a higher-end Rockchip RK3399 powered Android 7.1 TV box or mini PC, and Zidoo will also sell it as a single board computer for custom projects in the field of robotics, automotive control, artificial intelligence and more. Zidoo M9 specifications: SoC – Rockchip RK3399 hexa-core processor with 2x Cortex-A72 cores @ 2.0GHz, 4x Cortex-A53 cores. and a Mali-T860MP4 GPU with support for OpenGL ES 1.1/2.0 /3.0, OpenVG1.1, OpenCL, and Directx11 System Memory – Dual-channel 4GB DDR (2GB is optional) Storage – 32GB eMMC5.1 flash (8GB/16GB/64G/128G […]

November 21, 2019 by Jean-Luc Aufranc (CNXSoft) - 8 Comments

Khadas VIM3 NPU ToolKit Release & Video Demo

Khadas VIM3 board based on Amlogic A311D processor with a 5TOPS Neural-network Processing Unit (NPU) launched last June. We’ve reviewed VIM3 with Android 9 shortly after launch, but until recently it was not possible to leverage the NPU since the software was not quite ready yet. The goods news is that Khadas has now released the NPU toolkit for both VIM3, and the cheaper VIM3L boards. The NPU toolkit contains the following directory: docs – Model conversion documentation acuity-toolkit – Model conversion tools linux_sdk – Linux SDK android_sdk – Android SDK The toolkit works in host PCs running Ubuntu 16.04 or 18.04 with Tensorflow framework, and inference can run on both Linux and Android OS in Khadas VIM3/3L board. It includes an Inception v3 sample with 299×299 sample photos, among other demos. You’ll find documentation to get started with model conversion and inference in Linux on Khadas Wiki. You can […]

November 20, 2019 by Jean-Luc Aufranc (CNXSoft) - 4 Comments

Centaur Unveils an x86 SoC with Integrated AI Coprocessor

Artificial intelligence is handled at different levels in the ecosystem with ultra-powerful systems in the cloud equipped with dedicated hardware such as FPGA or GPU cards, while on the other side of the spectrum we have Arm or RISC-V based processor with AI accelerator for low power systems like smartphones or battery-powered smart cameras. Centaur Technology aims to provide a solution catering to the middle segment of devices that don’t need ultra-low power consumption, nor the highest possible peak performance, but still require a relatively compact form factor and low costs. Their solution is a still-unnamed octa-core x86 processor featuring Centaur NCORE AI coprocessor. SoC with built-in NPU (Neural-network Processing Unit) is pretty common in the Arm and RISC-V world, but it’s apparently a world’s first in the x86 space since existing solutions are all based on external accelerators. Key features of the Centaur x86 AI processor: x86 microprocessor with […]

November 19, 2019 by Ayo Ayibiowu - 8 Comments

Bangle.js is an Hackable, Open Source JavaScript and TensorFlow-driven Smartwatch (Crowdfunding)

Espruino brought JavasScript to the Microcontroller, now Bangle.js is bringing Javascript plus TensorFlow Lite to your smartwatch. There has been some movement by some developers that says that JavaScript should be used for everything, even though I find that idea ridiculous, I still find JavaScript a fascinating language. The NeaForm Research team and Gordon Williams (the brain behind Espruino) have all teamed up in launching Bangle.js Smartwatch. Bangle.js isn’t your ordinary smartwatch, at the heart of it is the open-source ecosystem. JavaScript plus TensorFlow Lite and of course, a cool looking Smartwatch is what Bangle.js is offering. Bangle.js was launched at the recently concluded NodeConf EU conference, and the goal is to bootstrap an Open Health Platform hopefully. NodeWatch is the specific implementation of Bangle.js for NodeConf EU 2019, co-developed by Espruino and NearForm Research. This project has the potential to bootstrap a community-driven open health platform where anyone can […]

November 19, 2019November 20, 2019 by Jean-Luc Aufranc (CNXSoft) - 33 Comments

Orange Pi 4/4B SBC Comes with Rockchip RK3399 SoC, Gyrfalcon 2801S NPU

Shenzhen Xunlong Software’s Orange Pi RK3399 single board computer launched in early 2018 with 2GB RAM for $109, and earlier this year, the company launched an updated version with 4GB RAM and a lower $99.96 price tag. But there are plenty Rockchip RK3399 SBC’s on the market, including FrienglyELEC NanoPi M4 going for $50 and up ($75 with 4GB RAM), and Pine64 RockPro64 board starting at $59.99 with 2GB RAM, and $79.99 with 4GB. So unless you need the extra features (HDMI Input, SATA port, mPCIe socket…) offered by Orange Pi RK3399, other boards may be more competitive. So the company has been working on lowering the cost with a smaller board. Meet Orange Pi 4. They’ve also provided some extra features with a variant of the board called Orange Pi 4B that adds a Gyrfalcon Lightspeeur 2801S AI accelerator chip/NPU. That says a lot that neither Rockchip RK3399Pro SoC […]

November 18, 2019 by Jean-Luc Aufranc (CNXSoft) - 2 Comments

Lightspeeur 5801 AI Accelerator Delivers 2.8 TOPS at 224 mW of Power

Announced in 2017, Gyrflacon LightSpeeur 2801 AI Accelerator could deliver 2.8 TOPS at 0.3 Watts of power. It’s now found in Orange Pi AI Stick Lite computer stick selling for around $20. Since then the company released 2802 chip for IoT applications, and earlier this year, the company introduced Gyrfalcon 2803 yielding up to 16.8TOPS @ 700 mW for “advanced edge” applications, and they’ve now announced Lightspeeur 5801 chip delivering 2.8 TOPS at 224 mW of power, or 12.6 TOPS/W. That does not seem much of any improvement of Lightspeeur 2801 since peak performance is the same, and power only slightly lower, but let’s check out more details to find out if there’s more to it. Key features: Based on the Gyrfalcon Matrix Processing Engine Performance – Up to 12.6 TOPs/Watt, peak: 2.8 TOPS @ 200 MHz Power Consumption – 224 mW @ 2.8 TOPs Latency – < 4 ms […]