How to implement edge AI? Experts from NXP and Alibaba DAMO Academy offer you advice!
With the development of artificial intelligence/machine learning algorithms, related technologies are used in more and more application scenarios. How to migrate the trained model to the embedded end and implement fast and reliable reasoning on the edge has become a key technical point in the engineering field.
In order to meet such design requirements, NXP provides a comprehensive portfolio of microcontrollers and microprocessors, which are widely used in industrial and consumer scenarios. At the same time, NXP also provides a processor machine learning algorithm tool chain to make the implementation of edge AI projects "smooth as silk"!
In this lecture, algorithm and engineering experts from NXP and Alibaba DAMO Academy will jointly explain in detail how to make full use of the technical resources of machine learning and edge computing to accelerate the realization of edge inference. Through this lecture, everyone can not only understand the key technical features of NXP's low-power microcontrollers and eIQ machine learning tool chain, but also deeply understand the challenges and countermeasures of migrating artificial intelligence algorithms from servers or clouds to embedded devices for edge inference through cutting-edge face recognition application examples.
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