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Deploying artificial neural networks on resource-constrained MCUs poses significant challenges. STMicroelectronics addresses these with AI tools that optimize neural network execution on Arm Cortex-M based STM32 MCUs, offering up to 60% performance improvement and 20% memory footprint reduction. The talk showcases seamless benchmarking via the Developer Cloud and accelerated AI project development using the model zoo, Python wrappers, and Jupyter notebooks.
00:00 Welcome & Meet the Presenters
02:30 Talk Start
05:30 STM32 Cube.AI
13:55 Hands-on session
56:20 Q&A
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