Difference between revisions of "Neural Compute Stick (NCS)"

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[http://www.youtube.com/results?search_query=Movidius+Neural+Compute+Stick YouTube search...]
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[https://www.youtube.com/results?search_query=Movidius+Neural+Compute+Stick+NCS+Neural+Compute+Stick YouTube]
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[https://www.quora.com/search?q=Movidius%20Neural%20Compute%20Stick%20NCS%20Neural%20Compute%20Stick ... Quora]
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[https://www.google.com/search?q=Movidius+Neural+Compute+Stick+NCS+Neural+Compute+Stick ...Google search]
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[https://news.google.com/search?q=Movidius+Neural+Compute+Stick+NCS+Neural+Compute+Stick ...Google News]
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[https://www.bing.com/news/search?q=Movidius+Neural+Compute+Stick+NCS+Neural+Compute+Stick&qft=interval%3d%228%22 ...Bing News]
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* [[Intel]]
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* [[Development]] ... [[Notebooks]] ... [[Development#AI Pair Programming Tools|AI Pair Programming]] ... [[Codeless Options, Code Generators, Drag n' Drop|Codeless]] ... [[Hugging Face]] ... [[Algorithm Administration#AIOps/MLOps|AIOps/MLOps]] ... [[Platforms: AI/Machine Learning as a Service (AIaaS/MLaaS)|AIaaS/MLaaS]]
 
* [http://www.amazon.com/Intel-NCSM2450-DK1-Movidius-Neural-Compute/dp/B076751BN8/ref=sr_1_2?ie=UTF8&qid=1529346109&sr=8-2&keywords=Movidius+Neural+Compute+Stick Intel NCSM2450.DK1 Movidius Neural Compute Stick | Buy on Amazon.com]
 
* [http://www.amazon.com/Intel-NCSM2450-DK1-Movidius-Neural-Compute/dp/B076751BN8/ref=sr_1_2?ie=UTF8&qid=1529346109&sr=8-2&keywords=Movidius+Neural+Compute+Stick Intel NCSM2450.DK1 Movidius Neural Compute Stick | Buy on Amazon.com]
 
* [http://developer.movidius.com/ Developer]
 
* [http://developer.movidius.com/ Developer]
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* [[Google AIY Projects Program]]
  
The Movidius Neural Compute Stick is a miniature deep learning hardware development platform that you can use to prototype, tune, and validate, your AI programs, specifically Deep Neural Networks. It features the same Movidius vision processing unit (VPU) used to bring machine intelligence to drones, surveillance cameras, and VR or AR headsets now, in a USB stick form factor.
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The Movidius Neural Compute Stick is a miniature deep learning hardware [[development]] platform that you can use to prototype, tune, and validate, your AI programs, specifically Deep [[Neural Network]]s. The Movidius Neural Compute Stick is a USB device that allows you to run [[Deep Learning]] models on the edge, without requiring an internet connection or a powerful GPU. It is powered by the Intel Movidius Myriad 2 Vision Processing Unit (VPU), which can perform over 100 gigaflops of computation within a 1W power envelope1. You can use it to prototype and deploy AI applications for various domains, such as Computer [[Vision]], [[Natural Language Processing (NLP)]], [[Speech Recognition]], and more. It features the same Movidius vision processing unit (VPU) used to bring machine intelligence to drones, surveillance cameras, and VR or AR headsets now, in a USB stick form factor. You can also use the Intel Movidius Neural Compute SDK (NCSDK) to program and optimize your models for the device.  
  
 
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Latest revision as of 20:37, 26 April 2024

YouTube ... Quora ...Google search ...Google News ...Bing News

The Movidius Neural Compute Stick is a miniature deep learning hardware development platform that you can use to prototype, tune, and validate, your AI programs, specifically Deep Neural Networks. The Movidius Neural Compute Stick is a USB device that allows you to run Deep Learning models on the edge, without requiring an internet connection or a powerful GPU. It is powered by the Intel Movidius Myriad 2 Vision Processing Unit (VPU), which can perform over 100 gigaflops of computation within a 1W power envelope1. You can use it to prototype and deploy AI applications for various domains, such as Computer Vision, Natural Language Processing (NLP), Speech Recognition, and more. It features the same Movidius vision processing unit (VPU) used to bring machine intelligence to drones, surveillance cameras, and VR or AR headsets now, in a USB stick form factor. You can also use the Intel Movidius Neural Compute SDK (NCSDK) to program and optimize your models for the device.