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Connecting Edge AI Software with PyTorch, TensorFlow Lite, and ONNX Models

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Manage episode 367432837 series 3488687
Content provided by EdgeCortix Inc.. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by EdgeCortix Inc. or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://player.fm/legal.

By Antonio Nevado.
Data scientists and others may have concerns moving PyTorch, TensorFlow, and ONNX models to edge AI software applications – MERA makes it easy and is model-agnostic.
PyTorch, TensorFlow, and ONNX are familiar tools for many data scientists and AI software developers. These frameworks run models natively on a CPU or accelerated on a GPU, requiring little hardware knowledge. But ask those same folks to move their applications to edge devices, and suddenly knowing more about AI acceleration hardware becomes essential – and perhaps a bit intimidating for the uninitiated.
Read the full blog here

  continue reading

6 episodes

Artwork
iconShare
 
Manage episode 367432837 series 3488687
Content provided by EdgeCortix Inc.. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by EdgeCortix Inc. or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://player.fm/legal.

By Antonio Nevado.
Data scientists and others may have concerns moving PyTorch, TensorFlow, and ONNX models to edge AI software applications – MERA makes it easy and is model-agnostic.
PyTorch, TensorFlow, and ONNX are familiar tools for many data scientists and AI software developers. These frameworks run models natively on a CPU or accelerated on a GPU, requiring little hardware knowledge. But ask those same folks to move their applications to edge devices, and suddenly knowing more about AI acceleration hardware becomes essential – and perhaps a bit intimidating for the uninitiated.
Read the full blog here

  continue reading

6 episodes

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