The Movidius™ Neural Compute Stick is a new device for developing and deploying deep learning algorithms at the edge. Movidius created the Neural Compute Stick (NCS) to make deep learning application development on specialized hardware even more widely available.
The NCS is powered by the same low-power Movidius Vision Processing Unit (VPU) that can be found in millions of smart security cameras, gesture-controlled autonomous drones, and industrial machine vision equipment, for example. The convenient USB stick form factor makes it easier for developers to create, optimize and deploy advanced computer vision intelligence across a range of devices at the edge.
The USB form factor easily attaches to existing hosts and prototyping platforms, while the VPU inside provides machine learning on a low-power deep learning inference engine. You start using the NCS with trained Caffe framework-based feed-forward Convolutional Neural Network (CNN), or you can choose one of our example pre-trained networks. Then, by using our Toolkit, you can profile the neural network, then compile a tuned version ready for embedded deployment using our Neural Compute Platform API.
Here are some of its key features:
- Supports CNN profiling, prototyping, and tuning workflow
- All data and power provided over a single USB Type A port
Real-time, on device inference – cloud connectivity not required
- Run multiple devices on the same platform to scale performance
- Quickly deploy existing CNN models or uniquely trained networks
At the Intel Movidius team, we’re inspired by the incredible sophistication of the human brain’s visual system, and I’d like to think we’re getting a little closer to matching its capabilities with our new Neural Compute Stick.
To get started, you can visit developer.movidius.com for more info – let us know what you think by dropping feedback on the @movidius channel. The Movidius Neural Compute Toolkit takes offline deep learning inference applications deployment to places never gone before.
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