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Neuromorphic Computing Market Technology and Rising Demand For Artificial Intelligence

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Neuromorphic computing or neuromorphic engineering has been described as the use of large integration systems containing numerous analog circuits allowing the replication of neuro-biological behaviors existing in a human's nervous system. The neuromorphic computing market platform consists of two vital systems based on the custom hardware architecture. Such systems are designed to program neural microcircuits by applying brain-like thought process in cognitive computing and machine learning process. This procedure enables a machine to learn, adapt and function like a human brain does rather than functioning like a normal computer. In addition, to perform such a complex task, the computing platform requires the state-of-the-art circuit technologies and electronic components, which allows the platform to receive new data or knowledge gained from various other sources of neuroscience research, e.g.


Cloud Bursting for the World's Largest Consumer Market

Communications of the ACM

Cloud infrastructure is information technology consisting of various hardware resources and software technologies. It enables ubiquitous access to shared pools of configurable system resources and higher-level services that can be delivered with minimal management effort, often through the Internet. Cloud infrastructure today is a critical platform for many applications, providing basic support for the development of emerging areas, including big data, the Internet of Things (IoT), and artificial intelligence (AI). In 2016, International Data Corporation's Cloud Computing Survey reported cloud technology is becoming a staple of organization infrastructure, as 70% of organizations have at least one application in the cloud, and 56% of organizations are still identifying IT operations as candidates for cloud hosting.1 In 2017, IDC predicted that by 2021, spending on cloud infrastructure and cloud-supported hardware, software, and services would double to more than $530 billion.2


November 2019, Fog Computing for Industrial Automation Market Report by Sales, Revenue, Regional Analysis, Company Share, Market Size Foreacst till 2026 - The Chicago Sentinel

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Various types of elements such as interactions, research findings, interviews, sales, distribution medium, industrial supply chain, conclusion, appendix and source of data are identified in the report . We offer a scalable range of specialized industry-based reports along with with market trends report options ideal for numerous business needs. Based on graphs, charts and other formats our report help companies better comprehend their market trend data. Our analysis is performed on primary and secular trends related to a business's specific market, compiled into a customized study format based on your choice. Included key insights keep businesses appraised of the trends developing in the target market.


Multi-access Edge Computing (MEC) Market Growth Factors and Business Development Strategy from 2019-2025 Nokia, Intel, Hewlett Packard Enterprise – All - All Times Tech - UrIoTNews

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The Multi-access Edge Computing (MEC) report presents data and information associated with the economy meticulously and understandably from 2019-2025. It offers predictions and global Multi-access Edge Computing (MEC) market statistics which are calculated utilizing advanced secondary and primary research techniques. It features segmental Multi-access Edge Computing (MEC) investigation of the market where the focus is really on sections by product and application. Additionally, it supplies a thorough analysis of growth, considering market opportunities. The Multi-access Edge Computing (MEC) landscape is focused upon with viability of top organizations operating in the market.


Tensorflow benchmark Tesla instances

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LeaderGPU is a new player in the GPU computing market, and it intends to change the rules of the game. At this moment in time, the GPU computing market comprises several large players such as Amazon AWS, Google Cloud, etc. However, a large player does not always mean the best market offer. The LeaderGPU project, in comparison to Amazon AWS and Google Cloud, provides physical servers, not VPS, where hardware resources can be shared among several dozens of users. Tests were conducted on the LeaderGPU Tesla computing systems on synthetic data of the following network models: ResNet-50, ResNet-152, VGG16 and AlexNet.