tensorflow News - Page 12 of 16 - CNX Software

January 26, 2020January 26, 2020 by Jean-Luc Aufranc (CNXSoft) - 4 Comments

ESP Open Source Research Platform Enables the Design of RISC-V & Sparc SoC’s with Accelerators

FOSDEM 2020 will take place next week, and there will be several interesting talks about open-source hardware and software development. One of those is entitled “Open ESP – The Heterogeneous Open-Source Platform for Developing RISC-V Systems” with an excerpt of the abstract reading: ESP is an open-source research platform for RISC-V systems-on-chip that integrates many hardware accelerators. ESP provides a vertically integrated design flow from software development and hardware integration to full-system prototyping on FPGA. For application developers, it offers domain-specific automated solutions to synthesize new accelerators for their software and map it onto the heterogeneous SoC architecture. For hardware engineers, it offers automated solutions to integrate their accelerator designs into the complete SoC. If we go to the official website, we can see ESP (Embedded Scalable Platform) actually supports both 32-bit Leon3 (Sparc) and 64-bit Ariane (RISC-V) cores, and various hardware accelerators from the platform or third parties. Highlights: […]

January 13, 2020January 13, 2020 by Jean-Luc Aufranc (CNXSoft) - 1 Comment

SolidRun Janux GS31 Edge AI Server Combines NXP LX2160A & i.MX 8M SoCs with 128 Gyrfalcon AI Accelerators

SolidRun Janux GS31-Edge AI Inference Server

AI inference used to happen exclusively in powerful servers hosted in the cloud, but in recent years great efforts have been made to move inference at the edge, usually meaning on-device, due to much lower latency, and improved privacy. On-device inference works, but obviously, performance is limited, and on battery-operated devices, one also has to consider power consumption. So for some applications, it makes sense to have a local server with much more processing power than devices, and lower latency than the cloud. That’s exactly the use case SolidRun Janux GS31 Edge AI inference server is trying to target using several NXP processors combined with up to 128 Gyrfalcon Lightspeeur SPR2803 AI accelerators Janux GS31 server specifications: CPU Module – CEx7 LX2160A COM Express module with NXP LX2160A 16-core Arm Cortex A72 processor @ 2.0 GHz System Memory – Up to 64GB DDR4 RAM via 2x SO-DIMM sockets “Video” Processors […]

January 13, 2020January 13, 2020 by Jean-Luc Aufranc (CNXSoft) - No Comments

Getting Started with Amlogic NPU on Khadas VIM3/VIM3L

Shenzhen Wesion released the NPU toolkit for Khadas VIM3/VIM3L last November, so I decided to try the latest Ubuntu 18.04 image and the NPU toolkit on Khadas VIM3L, before switching to VIM3 for reasons I’ll explain below. I’ve followed two tutorials from the forum and wiki to run pre-built samples and then building a firmware image and samples from source. Khadas VIM3L and VIM3 Have Different & Optional NPUs This will be obvious to anyone who read the specs for Khadas VIM3 and VIM3L that the former comes with a 5 TOPS NPU, while the one in the latter only delivers up to 1.2 TOPS. But somehow, I forgot about this, and assume both had the same NPU making VIM3L more attractive but this type of task, Obviously I was wrong. But the real reason I stopped using Khadas VIM3L can be seen in the photo below. My board is […]

January 7, 2020January 7, 2020 by Jean-Luc Aufranc (CNXSoft) - No Comments

Raspberry Pi 4 Powered Open Source Hardware Robot Paves the Way for Robot Maids

Raspberry Pi 4 Open Source Hardware Robot

Eventually, we all expect robots to do chores and other manual tasks performed by humans such as preparing and serving food at restaurants, carry objects over rough terrain as opposed to just inside the warehouse with a flat floor, or even moves pieces on a chessboard when other humans are no here to play with us. I’m fully expecting to eventually own a robot maid of sorts to wash dishes, mop the floors, and perform other tasks on my behalf. We are not there yet, but Raspberry Pi 4 powered Pollen Robotics’ Reachy open source-hardware robot is getting us closer to the goal as it can handle small objects and via two robotic arms and a dual-camera head, and can also interact with humans using a microphone and a speaker. Key features and specifications of Reachy robot: Main body SBC – Raspberry Pi 4 SBC with 2GB according to a […]

January 3, 2020October 17, 2020 by Jean-Luc Aufranc (CNXSoft) - 2 Comments

Google Coral mPCIe and M.2 Cards for Sale, New Coral Dev Board Mini and Modules Coming in 2020

Google introduced Coral development board and USB accelerator with Google Edge TPU last year. The development board was comprised of a baseboard and Coral system-on-module with an NXP i.MX 8M quad-core Arm Cortex-A53 processor and the Edge TPU. Since then ASUS announced Tinker Edge T and CR1S-CM-A SBC based on the Coral module, and yesterday, I noticed Seeed Studio started selling mPCIe and M.2 AI accelerator card with Google Edge TPU, while today, Google announced upcoming Coral products for 2020. Coral Mini PCIe and M.2 Accelerators Coral Mini PCIe card specifications: Half-mini PCIe card with PCIe Gen2 x1 Supply voltage – 3.3VDC +/- 10 % Dimensions – 30.00 x 26.80 x 2.55 mm Weight – 3.6 g Temperature Range – Storage: -40 ~ 85°C; operating: -20 ~ 70°C Relative humidity – 0 ~ 100% (non-condensing) Op-shock – 100 G, 11ms (persistent); 1000 G, 0.5 ms (stress); 1000 G, 1.0 ms […]

December 26, 2019June 9, 2020 by Siji Sunny - No Comments

MediaPipe is an Open Source Perception Pipeline Framework Developed by Google

MediaPipe is an open-source perception pipeline framework introduced by Google, which helps to build multi-modal machine learning pipelines. A developer can build a prototype, without really getting into writing machine learning algorithms and models, by using existing components. This framework can be used for various vision & media processing applications (especially in VR) such as Object Detection, Face Detection, Hand Tacking, Multi-hand Tracking and Hair Segmentation. MediaPipe supports various hardware and operating system platforms such as Android, iOS & Linux by offering API’s in C++, Java, Objective-c, etc. And this framework also capable of utilizing GPU resources. MediaPipe Components The framework is comprised of three major components A framework for inference from the pipeline data Tools for evaluation And a collection of reusable inference and processing components It follows the approach of Graph-based frameworks in OpenCV and all processing happens with the context of the Graph. The Graph contains a […]

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 […]

October 21, 2019September 2, 2020 by Stephen Vicinanza - No Comments

AAEON M.2 and mPCIe Cards for AIoT Acceleration Run Kneron KL520 AI SoC

The AAEON announcement of its AI Acceleration M.2 and mini-PCIe cards AAEON uses Kneron KL520 AI SoC dual Cortex-M4 on a series of new modules that are accelerating AI edge computing and that only need 0.5 Watt of power. The modules are M.2 and mini-PCIe AI acceleration cards, that offer a new way to come at AI acceleration. What AI Features are Enhanced The cards are meant to enhance and accelerate AI functions, like gesture detection, facial and object recognition, driver behavior in such AIoT areas as access control, automation, and security. History of the AAEON Development Previously AAEON has been offering the M.2 and mini-PCIe AI core modules for the Boxer computers that are based on the Intel Movidius Myriad 2 and Myriad X Vision Processing Units (VPU). Reporting was done on these previous releases in the articles on the UP AI core mini-PCIe card and the AI Core […]