Issue link: https://resources.mouser.com/i/1442826
20 AI s director of AI/ML technologies for NXP, I'm very excited to announce the general availability of NXP's eIQ™ machine learning (ML) software development environment. eIQ ML software is available now with inference engines and libraries leveraged from the tremendous advancements in open source machine learning technologies. NXP has deployed and optimized these technologies, such as CMSIS-NN, TensorFlow, TensorFlow Lite, OpenCV, and Arm NN, for our popular i.MX RT and i.MX applications processors, and are easily accessed through NXP's development environments for MCUXpresso and Yocto (Linux) to provide seamless support for your application development. Furthermore, eIQ software is accompanied by sample applications in object detection and voice recognition to provide designers with a starting point in their deployment of machine learning at the edge. As ML and Artificial Intelligence (AI) migrates towards the edge, one of the biggest challenges is deployment on resource- constrained devices, especially if you've been building your ML applications in the cloud. To run your models directly on edge devices, those models must be optimized and matched to an inference engine supporting the specific compute engines (i.e., CPU, GPU, DSP, ML accelerator). eIQ ML software solves this challenge, making it easy for you to integrate complex hardware components and providing the expertise for machine learning vision and voice applications. Unlock Machine Learning on Edge Devices with eIQ ™ Software Development Environment By Markus Levy, NXP Director of AI and Machine Learning Technologies A ❝ ❞ Machine Learning is on the rise, but it's just the tip of the iceberg.