We held our tinyML Vision Challenge! Thank you for joining us to hear how Intel and Luxonis have come together to offer an advanced intelligent camera platform called DepthAI.
The platform is powered by the Intel® Movidius™ Myriad™ X Vision Processing Unit offering depth perception and AI inference acceleration in a small embedded form-factor device the LUX-ESP32. The LUX-ESP32 supports a USB-C connection to a single board computer or operates standalone making it a great, low-power option for the tinyML Vision Challenge. We will discuss how to start developing vision-based spatial edge solutions using Luxonis’ DepthAI software and AI with Intel’s OpenVINO™ toolkit. And how easy it is to get started with the OpenVINO™ toolkit by registering to use Intel’s cloud developer environment called the Intel® DevCloud for the Edge, which is free to access, always installed with the OpenVINO™ toolkit, and a great way to learn AI inference through Jupyter Notebook experiences. And if you need pre-trained models for use case development you can source 100+ pre-trained models from the Intel Open Model Zoo on Github.
Academic Program Manager at Intel who has been working in the embedded, automotive, and Internet of Things industry for 20+ years. He is passionate about advocating for AI developers, students and faculty to help them advance their knowledge using Intel Technologies such as the AI toolkit called Intel®️ Distribution of OpenVINO™️ toolkit, learning through Intel’s new Edge AI Certification program, and prototyping ideas inside the cloud developer environment Intel® DevCloud for the Edge.
Software developer at Luxonis. Eric is an open-source enthusiast who loves coding, helping other engineers, solving challenges, and anything related to technology and science.
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Jay Burris / Erik Kokalj
Feel free to ask your questions on this thread and keep the conversation going!