artificial intelligence News - Page 84 of 104 - CNX Software

August 6, 2019 by Jean-Luc Aufranc (CNXSoft) - 34 Comments

TensorFlow Lite for Microcontrollers Benchmarked on Linux SBCs

TensorFlow Lite microcontrollers benchmark linux SBC

Dimitris Tassopoulos (Dimtass) decided to learn more about machine learning for embedded systems now that the technology is more mature, and wrote a series of five posts documenting his experience with low-end hardware such as STM32 Bluepill board, Arduino UNO, or ESP8266-12E module starting with simple NN examples, before moving to TensorFlow Lite for microcontrollers. Dimitris recently followed up his latest “stupid project” (that’s the name of his blog, not being demeaning here :)) by running and benchmarking TensorFlow Lite for microcontrollers on various Linux SBC. But why? you might ask. Dimitris tried to build tflite C++ API designed for Linux, but found it was hard to build, and no pre-built binary are available except for x86_64. He had no such issues with tflite-micro API, even though it’s really meant for baremetal MCU platforms. Let’s get straight to the results which also include a Ryzen platform, probably a laptop, for […]

August 5, 2019August 5, 2019 by Jean-Luc Aufranc (CNXSoft) - 6 Comments

Pine64 SoEdge-RK1808 AI Module Delivers 3.0 TOPS via Rockchip RK1808 SoC

SOPINE Model A Baseboard + SoEdge-RK1808

A few weeks ago, Ameridroid reported Pine64 would soon launch SoRock and SoEdge systems-on-module, but at the time there was virtually no info except SoRock would be likely based on either RK3328 or RK3399 and work on the existing Clusterboard, while SoEdge would be an AI Neural module for Artificial Intelligence tasks, with up to 3 TeraFLOPS of performance. I did not write about it at the time, simply because there was so little information, but this morning I’ve just received some photos of SoEdge-RK1808 module fitted to a baseboard that looks to be SOPINE Model “A” carrier board. SoEdge-RK1808 SoM Let’s try to derive the specifications from the photos even though some components appear to be blurred out or just unclear: SoC – Rockchip RK1808 dual-core Cortex-A35 processor with 3.0 TOPS NPU (Neural Processing Unit) System Memory – 2GB RAM (2x 8GBit Micro DDR4-2400) but limited PC-2133 Storage – […]

August 3, 2019 by Stephen Vicinanza - No Comments

Actcast Combines IFTTT-like Service with AI and Raspberry Pi 3 / Zero

In a report on April 30, 2017, Idein had developed GPGPU accelerated object recognition for the Raspberry Pi platform. That development led to the beta release of the ActCast IoT platform, which was announced on July 29, 2019, and uses deep learning algorithms for object and subject recognition. The program is for use with IoT and AI. The idea is to increase performance and link the system to the web for even more solutions. What it Does The use of physical world information in IoT projects has many applications. Such as a doorbell that sees a person, can then recognize the person. Ultimately letting the user know over the web through a smartphone, the person should be let in. And then the system unlocks the door. So Actcast is a bit like IFTTT with artificial intelligence / computer vision capabilities. Edge Computing Bringing the source of data closer to the […]

August 1, 2019 by Jean-Luc Aufranc (CNXSoft) - 8 Comments

HuskyLens AI Camera & Display Board is Powered by Kendryte RISC-V Processor (Crowdfunding)

A couple of years ago, I reviewed JeVois-A33 computer vision camera powered by Allwinner A33 quad-core Cortex-A7 processor running Linux. The tiny camera would implement easy-to-use software for machine vision with features such as object detection, eye tracking, QR code and ArUco marker detection, and so on. The camera could handle the tasks at hand, but since it relied on purely software computer vision, there were lag for some of the demo applications including 500ms for single object detection, and up to 3 seconds for YOLO test with multiple object types using deep learning algorithms. That’s a bit slow for robotics project, and software solutions usually consume more than hardware accelerated ones. Since then, we’ve started to see low-cost SoC and hardware with dedicated hardware AI accelerators, and one of those is Kendryte K210 dual-core RISC-V processor with a built-in KPU Convolutional Neural Network (CNN) hardware accelerator and APU audio […]

July 27, 2019 by Stephen Vicinanza - 11 Comments

Alibaba Unveils XuanTie 910 16-core RISC-V Processor

When Pingtou Ge (Brother Pingtou) Semiconductor Co. was founded by Alibaba in September 2018, the vision was to create groundbreaking chips for production. The company had once been Zhongtianwei, a chip company, which was acquired by Alibaba in April 2018 along with team Aha. On July 25, 2019, it was announced that Brother Pingtou had released the XuanTie 910 (Black Iron 910) 16-Core RISC-V Processor. The company has reported that the processor will be integrated into high-performance end to end 5G chips, AI, and autonomous driving applications. There are conflicting reports that the processor is also known as T-Head, although its name means Black Iron. There has been no firm release date or price as of yet. Open-source technologies are being adopted on a regular basis in China, and the XuanTie 910 is being offered to developers with encouragement to use Berkeley-based open-source ISA with very few intellectual property restrictions. […]

July 13, 2019 by Jean-Luc Aufranc (CNXSoft) - No Comments

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

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, […]

July 12, 2019July 12, 2019 by Jean-Luc Aufranc (CNXSoft) - 4 Comments

MediaTek i700 Cortex-A75/A55 AI Processor to Power Automated Stores, Facial Recognition Applications

MediaTek has recently unveiled their i700 octa-core AI IoT Platform, which succeeds their little known MediaTek i500 (MT8385) processor, and features two Cortex-A75 cores, six Cortex-A55 cores, coupled with MediaTek APU 2.0 comprised of a dual-core AI processor, AI Accelerator and AI face detection engine that is said to offers 5x greater performance than the i500.. The new SoC also features an Imagination 9XM GPU clocked at 970MHz, as well as a tri-core ISP with support for a single 32MP camera or a 24MP+16MP dual-camera setup. MediaTek i700 key features & specifications: CPU – 6x Arm Cortex-A55 cores @ 2.0 GHz, 2x Arm Cortex-A75 cores @ 2.2 GHz GPU – Imagination PowerVR 9XM-HP8 (GM9446?) GPU @ 970 MHz MediaTek APU 2.0 AI engine – Dual-core AI processor, AI Accelerator, AI Face Detection Engine; Neuropilot SDK support Memory – Up to 8GB LPDDR4x, 1866MHz Connectivity Cellular – Carrier Aggregation (CA), CDMA2000 […]

July 3, 2019July 3, 2019 by Stephen Vicinanza - 1 Comment

GAPPoc AI development boards based on the GAP8 RISC-V Chip

GreenWaves has developed a development board based on the GAP8 chip which can be evaluated from a GAPuino board, a generic board that can run off a low power external power source or USB and is compatible with the Arduino ecosystem. Recently the company moved beyond the generic board to the GAPPoc, platform which stands for GAP8 Proof of Concept. The GAPPoc is focused on a class of applications which can be embedded on a single board and able to carry hardware such as crystal or external memory, sensors, a radio fit, and a battery. The board will be geared towards a set of low power functions for a particular class of applications. This is a family of boards designed to increase the range of abilities in edge Artificial Intelligence. At this time there is only a single board with a platform to enhance AI, targeting Computer Vision in the […]