Introducing the EON Tuner: Edge Impulse's New AutoML Tool for Embedded Machine Learning

Today we are excited to announce the launch of Edge Impulse's new auto machine learning tool, the EON Tuner! The EON Tuner helps you find and select the best embedded machine learning model for your application within the constraints of your target device. The EON Tuner analyzes your input data, potential signal processing blocks, and neural network architectures - and gives you an overview of possible model architectures that will fit your chosen device's latency and memory requirements. Curious to observe the EON Tuner in action? In this or this public project you can see the results returned by the EON Tuner in our ‘Responding to your voice’ datasets.


This is a companion discussion topic for the original entry at https://www.edgeimpulse.com/blog/introducing-the-eon-tuner-edge-impulses-new-automl-tool-for-embedded-machine-learning
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Congrats guys, it seems like it could greatly improve the accuracy of some projects, like the one shown by Jan on the demo video! I’m looking forward to seeing it come to other data types, specifically imagery, so that I can use it on my camera trap project :smiley:

Will follow this closely.

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Guys this is so cool.
AI for AI fantastic work.
But just one question.
Once I select a particular framework do I then need to retrain it to deploy or can I just go straight to deployment.
I think I answered my own question after trying to swap after deployment.
Yes you probably do. And that makes perfect sense. No point storing all those trained models.
If this is the case maybe the Retrain Model indication in the side bar should show that.

But still this IS the coolest thing since sliced bread.

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@greg_dickson No just click ‘set primary’ > ‘Deploy’ and done. All models are stored.