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Bottoms-up Approach to Building Extremely Small Models
Speaker: Blair Newman, Chief Technology Officer @ Neuton

Neural networks created today contain more and more coefficients and neurons and require ever-increasing processing power. A majority of neural networks are based on a predetermined architecture and during the optimization process, only neuron parameters undergo optimization, while the architecture itself remains predetermined. This is the main cause of the unnecessary growth of network size.

During this tech talk, we will show you how Neuton has taken a completely different approach resulting in models that are 1000x smaller and 1000x faster than other frameworks such as Tensorflow lite and Pytorch.

This talk is part of the bi-weekly AI Virtual Tech Talk Series: https://developer.arm.com/solutions/machine-learning-on-arm/ai-virtual-tech-talks

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Sep 7, 2021 04:00 PM in London

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