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The Evolution of Deep Learning Architectures on the Edge
The evolution in use cases and deep learning architectures as just a couple of examples all these things impact the hardware. The question really becomes, is your architecture generic enough to be able to support new and upcoming algorithms? And can it go beyond convolutions into complex Architecture like large language models and recommendations engines, which have been quite popular these days. So these are some of the questions and debates we ask ourselves,. We try to enable both depending upon the vertical of interest vertical element is a specific form factor of interest could be mobile in nature could be automotive in nature.