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About
Build advanced embedded machine learning applications without a PhD. Collect sensor, audio, or camera data directly from devices, files, or cloud integrations to build custom datasets. Leverage automatic labeling tools from object detection to audio segmentation. Set up and run reusable scripted operations that transform your input data on large sets of data in parallel by using our cloud infrastructure. Integrate custom data sources, CI/CD tools, and deployment pipelines with open APIs. Accelerate custom ML pipeline development with ready-to-use DSP and ML algorithms. Make hardware decisions based on device performance and flash/RAM every step of the way. Customize DSP feature extraction algorithms and create custom machine learning models with Keras APIs. Fine-tune your production model with visualized insights on datasets, model performance, and memory. Find the perfect balance between DSP configuration and model architecture, all budgeted against memory and latency constraints.
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About
GPUs bring data in and out quickly, but have little locality of reference because of their small caches. They are geared towards applying a lot of compute to little data, not little compute to a lot of data. The networks designed to run on them therefore execute full layer after full layer in order to saturate their computational pipeline (see Figure 1 below). In order to deal with large models, given their small memory size (tens of gigabytes), GPUs are grouped together and models are distributed across them, creating a complex and painful software stack, complicated by the need to deal with many levels of communication and synchronization among separate machines. CPUs, on the other hand, have large, much faster caches than GPUs, and have an abundance of memory (terabytes). A typical CPU server can have memory equivalent to tens or even hundreds of GPUs. CPUs are perfect for a brain-like ML world in which parts of an extremely large network are executed piecemeal, as needed.
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Platforms Supported
Windows
Not Supported
Mac
Not Supported
Linux
Not Supported
Cloud
Supported
On-Premises
Not Supported
iPhone
Not Supported
iPad
Not Supported
Android
Not Supported
Chromebook
Not Supported
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Platforms Supported
Windows
Not Supported
Mac
Not Supported
Linux
Not Supported
Cloud
Supported
On-Premises
Not Supported
iPhone
Not Supported
iPad
Not Supported
Android
Not Supported
Chromebook
Not Supported
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Audience
Developers in search of a soluion to build advanced embedded machine learning applications
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Audience
Companies doing AI and ML development
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Support
Phone Support
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24/7 Live Support
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Online
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Support
Phone Support
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24/7 Live Support
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Online
Supported
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API
Offers API
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API
Offers API
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Pricing
No information available.
Free Version
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Free Trial
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Pricing
No information available.
Free Version
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Free Trial
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Reviews/
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Reviews/
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Training
Documentation
Supported
Webinars
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Live Online
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In Person
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Training
Documentation
Supported
Webinars
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Live Online
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In Person
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Company InformationEdge Impulse
United States
edgeimpulse.com/product
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Company InformationNeural Magic
Founded: 2018
United States
neuralmagic.com
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Integrations
Ultralytics
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