At the start of last month I sat down to benchmark the new generation of accelerator hardware intended to speed up machine learning inferencing on the edge. So I’d have a rough yardstick for comparison, I also ran the same benchmarks on the Raspberry Pi. Afterwards a lot of people complained that I should have been using TensorFlow Lite on the Raspberry Pi rather than full blown TensorFlow. They were right, it ran a lot faster.
Then with the release of the AI2GO framework from Xnor.ai, which uses next generation binary weight models, I looked at the inferencing speeds of these next generation of models in comparison to ‘traditional’ TensorFlow. This also ran a lot faster.
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