artificial intelligence (AI) News - Page 116 of 121 - CNX Software

January 4, 2018 by Jean-Luc Aufranc (CNXSoft) - 3 Comments

Samsung Announces Exynos 9810 Octa-core Processor Optimized for AI and Multimedia Applications

Samsung Electronics has just announced the launch of Exynos 9 Series 9810 (Exynos 9810) manufactured with Samsung’s 10-nm FinFET process, featuring an eight core processor clocked up to 2.9 GHz, a gigabit (1.2 Gbps) LTE modem and deep learning-enhanced image processing. Single core performance is aud to be improved by two-fold, while multi-core performance gets a 40% improvement compared to the previous generation chip, which should be Exynos 8895. ARM Mali-G72 GPU is said to bring more realistic graphics along with 20% more performance. Samsung Exynos 9810 specifications with extra cache and memory info from Anandtech: CPU Quad core custom Exynos M3 @ up to 2.9GHz optimized for performance; 512KB L2 cache per core Quad-core Arm Cortex-A55 @ up to 1.9GHz optimized for efficiency; 128KB L2 cache per core GPU – Arm Mali-G72MP18 Memory – LPDDR4x (4x 16-bit @ 1794 MHz) Storage – UFS 2.1, SD 3.0 Display – Up […]

January 3, 2018June 4, 2019 by Jean-Luc Aufranc (CNXSoft) - 3 Comments

Laceli AI Compute Stick is a More Powerful & Efficient Alternative to Intel/Movidius Neural Compute Stick

Intel’s Movidius Neural Compute Stick is a low power deep learning inference kit and “self-contained” artificial intelligence (A.I.) accelerator that connects to the USB port of computers or development boards like Raspberry Pi 3, delivering three times more performance than a solution accelerated with VideoCore IV GPU. So far it was the only A.I USB stick solution that I heard of, but Gyrfalcon Technology , a US startup funded at the beginning of last year, has developed its own “artificial intelligence processor” with Lightspeeur 2801S, as well as a neural USB compute stick featuring the solution: Laceli AI Compute Stick. The company claims Laceli AI Compute Stick runs at 2.8 TOPS (Trillion operation per second) performance within 0.3 Watt of power, which is 90 times more efficient than the Movidius USB Stick that can deliver 100 GFLOPS (0.1 TOPS) within 1 Watt of power. Information about the processor and stick […]

December 29, 2017 by Jean-Luc Aufranc (CNXSoft) - 1 Comment

Google Assistant SDK Now Supports Device Actions, More Languages (French, German, Japanese)

Back in May 2017, Google released the Assistant SDK that worked on Raspberry Pi 3, and other ARM boards, essentially transforming low cost development boards into Google Home equivalent. The SDK became more popular once Google’s AIY Voice Kit was launched since it offered an easy and inexpensive way to use it with Raspberry Pi 3 board. Since all you need was a Linux board with an Internet connection, a microphone, and speaker, I tried Google Assistant SDK on one of the cheapest platform available: Orange Pi Zero Set 6 Kit including Orange Pi Zero board, but also an expansion board with built-in microphone and audio output jack, and a cute little case. I added my own pair of speakers, micro SD card, and USB power supply, and after setting up the software, I was able ask question, and get answers with female voice using the demo app. At the […]

December 21, 2017December 21, 2017 by Jean-Luc Aufranc (CNXSoft) - 3 Comments

Qualcomm Developer’s Guide to Artificial Intelligence (AI)

Qualcomm has many terms like ML (Machine Learning), DL (Deep Learning), CNN (Convolutional Neural Network), ANN (Artificial Neural Networks), etc.. and is currently made possible via frameworks such as TensorFlow, Caffe2 or ONNX (Open Neural Network Exchange). If you have not looked into details, all those terms may be confusions, so Qualcomm Developer Network has released a 9-page e-Book entitled “A Developer’s Guide to Artificial Intelligence (AI)” that gives an overview of all the terms, what they mean, and how they differ. For example, they explain that a key difference between Machine Learning and Deep Learning is that with ML, the input features of the CNN are determined by humans, while DL requires less human intervention. The book also covers that AI is moving to the edge / on-device for low latency, and better reliability, instead of relying on the cloud. It also quickly go through the workflow using Snapdragon […]

December 7, 2017 by Jean-Luc Aufranc (CNXSoft) - 9 Comments

Qualcomm Snapdragon 845 Octa Core Kryo 385 SoC to Power Premium Smartphones, XR Headsets, Windows Laptops

Qualcomm Snapdragon 845 processor was expected since May 2017 with four custom Cortex A75 cores, four Cortex A53 cores, Adreno 630 GPU, and X20 LTE modem. with the launch planned for Q1 2018. At least, that what the leaks said. Qualcomm has now formally launched Snapdragon 845 Mobile Platform and rumors were mostly right, as the the octa-core processor comes with four Kryo 385 Gold cores (custom Cortex A75), four Kryo 385 Silver cores (custom Cortex A55) leveraging DynamIQ technology, an Adreno 630 “Visual Processing System”, and Snapdragon X20 modem supporting LTE Cat18/13. The processor is said to use more advanced artificial intelligence (AI) allowing what the company calls “extended reality (XR)” applications, and will soon be found in flagship smartphones, XR headsets, mobile PCs, and more. Qualcomm Snapdragon 845 (SDM845) specifications: Processor 4x Kryo 385 Gold performance cores @ up to 2.80 GHz (custom ARM Cortex A75 cores) 4x […]

December 4, 2017April 14, 2018 by Jean-Luc Aufranc (CNXSoft) - 12 Comments

Top 5 Most Powerful Arm SBCs & Development Boards in 2017 / Early 2018

Raspberry Pi, Orange Pi, and NanoPi boards among others are all great and inexpensive Arm Linux development boards that do good enough job for many tasks, but they may not cut it if you have higher requirements either in terms of CPU power, GPU capabilities and performance, I/O bandwidth, and in some cases software and support. So I’ve decided to make a list of 5 single board computers or development boards that I consider to be the most powerful in 2017, early 2018. I have limited the price to $1,000 maximum, the board must be easy to purchase for most people (e.g. you don’t need to be a tier-1 automotive supplier, or operate your own datacenter), and in case the board is not quite available yet, the likeliness of actual launch must be reasonably high. Those criteria for example exclude Intrinsyc Open-Q 835 development kit since it costs $1.149 and […]

December 1, 2017December 1, 2017 by Jean-Luc Aufranc (CNXSoft) - 2 Comments

$45 AIY Vision Kit Adds Accelerated Computer Vision to Raspberry Pi Zero W Board

AIY Projects is an initiative launched by Google that aims to bring do-it yourself artificial intelligence to the maker community by providing affordable development kits to get started with the technology. The first project was AIY Projects Voice Kit, that basically transformed Raspberry Pi 3 board into a Google Home device by adding the necessary hardware to support Google Assistant SDK, and an enclosure. The company has now launched another maker kit with AIY Project Vision Kit that adds a HAT board powered by Intel/Movidius Myriad 2 VPU to Raspberry Pi Zero W, in order to accelerate image & objects recognition using TensorFlow’s machine learning models. The kit includes the following items: Vision Bonnet accessory board powered by Myriad 2 VPU (MA2450) 2x 11mm plastic standoffs 24mm RGB arcade button and nut 1x Privacy LED 1x LED bezel 1x 1/4/20 flanged nut Lens, lens washer, and lens magnet 50 mil […]

November 30, 2017 by Jean-Luc Aufranc (CNXSoft) - 4 Comments

AWS DeepLens is a $249 Deep Learning Video Camera for Developers

Amazon Web Services (AWS) has launched Deeplens, the “world’s first deep learning enabled video camera for developers”. Powered by an Intel Atom X5 processor with 8GB, and featuring a 4MP (1080p) camera, the fully programmable system runs Ubuntu 16.04, and is designed expand deep learning skills of developers, with Amazon providing tutorials, code, and pre-trained models. AWS Deeplens specifications: SoC – Intel Atom X5 Processor with Intel Gen9 HD graphics (106 GFLOPS of compute power) System Memory – 8GB RAM Storage – 16GB eMMC flash, micro SD slot Camera – 4MP (1080p) camera using MJPEG, H.264 encoding Video Output – micro HDMI port Audio – 3.5mm audio jack, and HDMI audio Connectivity – Dual band WiFi USB – 2x USB 2.0 ports Misc – Power button; camera, WiFi and power status LEDs; reset pinhole Power Supply – TBD Dimensions – 168 x 94 x 47 mm Weight – 296.5 grams The […]