|
Movidius (company)
Movidius Ltd. was a company based in San Mateo, California, that designed low-power processor chips for computer vision. The company was acquired by Intel in September 2016, who continues to sell the company's products under the Movidius line. Company history Movidius was co-founded in 2005 by Sean Mitchell, David Moloney, and Val Muresan in Dublin, Ireland. Between 2006 and 2016, it raised nearly $90 million in capital funding. In May 2013, the company appointed Remi El-Ouazzane as CEO. In January 2016, the company announced a partnership with Google. Movidius has been active in Google's Project Tango, and in September 2016 it was announced that Intel planned to acquire the company. Products Myriad 2 The company's Myriad 2 chip is a manycore vision processing unit that can function on power-constrained devices. The ''Fathom'' is a USB stick containing a Myriad 2 processor, allowing a vision accelerator to be added to devices using ARM processors including PCs, drones, ro ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Intel
Intel Corporation is an American multinational corporation and technology company headquartered in Santa Clara, California, and Delaware General Corporation Law, incorporated in Delaware. Intel designs, manufactures, and sells computer components such as central processing units (CPUs) and related products for business and consumer markets. It is one of the world's List of largest semiconductor chip manufacturers, largest semiconductor chip manufacturers by revenue, and ranked in the Fortune 500, ''Fortune'' 500 list of the List of largest companies in the United States by revenue, largest United States corporations by revenue for nearly a decade, from 2007 to 2016 Fiscal year, fiscal years, until it was removed from the ranking in 2018. In 2020, it was reinstated and ranked 45th, being the List of Fortune 500 computer software and information companies, 7th-largest technology company in the ranking. It was one of the first companies listed on Nasdaq. Intel supplies List of I ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
ARM Architecture
ARM (stylised in lowercase as arm, formerly an acronym for Advanced RISC Machines and originally Acorn RISC Machine) is a family of reduced instruction set computer, RISC instruction set architectures (ISAs) for central processing unit, computer processors. Arm Holdings develops the ISAs and licenses them to other companies, who build the physical devices that use the instruction set. It also designs and licenses semiconductor intellectual property core, cores that implement these ISAs. Due to their low costs, low power consumption, and low heat generation, ARM processors are useful for light, portable, battery-powered devices, including smartphones, laptops, and tablet computers, as well as embedded systems. However, ARM processors are also used for desktop computer, desktops and server (computing), servers, including Fugaku (supercomputer), Fugaku, the world's fastest supercomputer from 2020 to 2022. With over 230 billion ARM chips produced, , ARM is the most widely used ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Vision Processing Unit
A vision processing unit (VPU) is (as of 2023) an emerging class of microprocessor; it is a specific type of AI accelerator, designed to accelerate machine vision tasks. Overview Vision processing units are distinct from graphics processing units (which are specialised for video encoding and decoding) in their suitability for running machine vision algorithms such as CNN (convolutional neural networks), SIFT (scale-invariant feature transform) and similar. They may include direct interfaces to take data from cameras (bypassing any off chip buffers), and have a greater emphasis on on-chip dataflow between many parallel execution units with scratchpad memory, like a manycore DSP. But, like video processing units, they may have a focus on low precision fixed point arithmetic for image processing. Contrast with GPUs They are distinct from GPUs, which contain specialised hardware for rasterization and texture mapping (for 3D graphics), and whose memory architecture is o ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Google Clips
Google Clips is a discontinued miniature clip-on camera device developed by Google. History It was announced during Google's "Made By Google" event on October 4, 2017. It was released for sale on January 27, 2018. With a flashing light emitting diode (LED) that indicates it is recording, Google Clips automatically captures video clips at moments its machine learning algorithms determine to be interesting or relevant. Google Clips' artificial intelligence (AI) will learn the faces of people so it can learn to take photos with certain people. Google Clips can automatically set lighting and framing. It had 16 GB of storage built-in storage and could record clips for up to 3 hours. This camera was originally priced at $249 in the United States. The product was pulled from the Google Store on October 15, 2019. Google has said that the product would be supported until the end of December 2021. Reception ''The Independent'' wrote that Google Clips is "an impressive little device, b ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Deep Neural Network
Deep learning is a subset of machine learning that focuses on utilizing multilayered neural network (machine learning), neural networks to perform tasks such as Statistical classification, classification, Regression analysis, regression, and representation learning. The field takes inspiration from Neuroscience, biological neuroscience and is centered around stacking Artificial neuron, artificial neurons into layers and "training" them to process data. The adjective "deep" refers to the use of multiple layers (ranging from three to several hundred or thousands) in the network. Methods used can be either Supervised learning, supervised, Semi-supervised learning, semi-supervised or Unsupervised learning, unsupervised. Some common deep learning network architectures include Fully connected network, fully connected networks, deep belief networks, recurrent neural networks, convolutional neural networks, Generative adversarial network, generative adversarial networks, Transformer (ma ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
OpenVINO
OpenVINO is an open-source software toolkit for optimizing and deploying deep learning models. It enables programmers to develop scalable and efficient AI solutions with relatively few lines of code. It supports several popular model formats and categories, such as large language models, computer vision, and generative AI. Actively developed by Intel, it prioritizes high-performance inference on Intel hardware but also supports ARM/ARM64 processors and encourages contributors to add new devices to the portfolio. Based in C++, it offers the following APIs: C/ C++, Python, and Node.js (an early preview). OpenVINO is cross-platform and free for use under Apache License 2.0. Workflow The simplest OpenVINO usage involves obtaining a model and running it as is. Yet for the best results, a more complete workflow is suggested: * obtain a model in one of supported frameworks, * convert the model to OpenVINO IR using the OpenVINO Converter tool, * optimize the model, using traini ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
TensorFlow
TensorFlow is a Library (computing), software library for machine learning and artificial intelligence. It can be used across a range of tasks, but is used mainly for Types of artificial neural networks#Training, training and Statistical inference, inference of Neural network (machine learning), neural networks. "It is machine learning software being used for various kinds of perceptual and language understanding tasks" – Jeffrey Dean, minute 0:47 / 2:17 from YouTube clip It is one of the most popular deep learning frameworks, alongside others such as PyTorch. It is free and open-source software released under the Apache License 2.0. It was developed by the Google Brain team for Google's internal use in research and production. The initial version was released under the Apache License 2.0 in 2015. Google released an updated version, TensorFlow 2.0, in September 2019. TensorFlow can be used in a wide variety of programming languages, including Python (programming language), P ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Deep Learning
Deep learning is a subset of machine learning that focuses on utilizing multilayered neural networks to perform tasks such as classification, regression, and representation learning. The field takes inspiration from biological neuroscience and is centered around stacking artificial neurons into layers and "training" them to process data. The adjective "deep" refers to the use of multiple layers (ranging from three to several hundred or thousands) in the network. Methods used can be either supervised, semi-supervised or unsupervised. Some common deep learning network architectures include fully connected networks, deep belief networks, recurrent neural networks, convolutional neural networks, generative adversarial networks, transformers, and neural radiance fields. These architectures have been applied to fields including computer vision, speech recognition, natural language processing, machine translation, bioinformatics, drug design, medical image analysis, c ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
FLOPS
Floating point operations per second (FLOPS, flops or flop/s) is a measure of computer performance in computing, useful in fields of scientific computations that require floating-point calculations. For such cases, it is a more accurate measure than measuring instructions per second. Floating-point arithmetic Floating-point arithmetic is needed for very large or very small real numbers, or computations that require a large dynamic range. Floating-point representation is similar to scientific notation, except computers use base two (with rare exceptions), rather than base ten. The encoding scheme stores the sign, the exponent (in base two for Cray and VAX, base two or ten for IEEE floating point formats, and base 16 for IBM Floating Point Architecture) and the significand (number after the radix point). While several similar formats are in use, the most common is ANSI/IEEE Std. 754-1985. This standard defines the format for 32-bit numbers called ''single precision'', a ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Video Surveillance
Closed-circuit television (CCTV), also known as video surveillance, is the use of closed-circuit television cameras to transmit a signal to a specific place on a limited set of monitors. It differs from broadcast television in that the signal is not openly transmitted, though it may employ point-to-point, point-to-multipoint (P2MP), or mesh wired or wireless links. Even though almost all video cameras fit this definition, the term is most often applied to those used for surveillance in areas that require additional security or ongoing monitoring (videotelephony is seldom called "CCTV"). The deployment of this technology has facilitated significant growth in state surveillance, a substantial rise in the methods of advanced social monitoring and control, and a host of crime prevention measures throughout the world. Though surveillance of the public using CCTV is common in many areas around the world, video surveillance has generated significant debate about balancing its use w ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Internet Of Things
Internet of things (IoT) describes devices with sensors, processing ability, software and other technologies that connect and exchange data with other devices and systems over the Internet or other communication networks. The IoT encompasses Electronic engineering, electronics, Telecommunications engineering, communication, and computer science engineering. "Internet of things" has been considered a misnomer because devices do not need to be connected to the public internet; they only need to be connected to a network and be individually addressable. The field has evolved due to the convergence of multiple technologies, including ubiquitous computing, commodity sensors, and increasingly powerful embedded systems, as well as machine learning.Hu, J.; Niu, H.; Carrasco, J.; Lennox, B.; Arvin, F.,Fault-tolerant cooperative navigation of networked UAV swarms for forest fire monitoring Aerospace Science and Technology, 2022. . Older fields of embedded systems, wireless sensor netw ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
