eXeL AI ™ Educational Benefits
eXeL AI ™ Educational Initiative
These products are focused on the education market, as we're aiming to address the gap between high school AI education and the projected industry growth and related AI/ML job opportunities. In many cases AI/ML is absent from curricula before master's degree programs; we simply provide a set of tools to enable education for any experience level and encourage earlier access to the technology for students. With educational curriculum submissions in Texas (TEKS), we are hoping to accelerate early AI/ML exposure for high school programming using computer vision to generate excitement around AI. Our plan is to continue expanding to schools across the country to help establish and then build on foundations in AI/ML education. We aim to add future robotics, mobility and sensor integrations, providing continued expansions for our kits.
eXeL AI ™ Kit Comparison Chart
Building on the TensorFlow Lite framework and Edge TPU processing capabilities, the eXeL AI ™ kit utilizes the Coral USB module from Google for accelerating ML inferencing speed and improving accuracy.
Coral from Google is a platform for bringing AI/ML to the edge with on-device ML inferencing acceleration. It uses Edge TPU technology designed by Google that is optimized for TensorFlow Lite machine learning models. The Coral USB Accelerator module that is an integral part of the eXeL AI ™ Kit has the Edge TPU inside with the USB3 interface speed with the Raspberry Pi host, and it provides 4 TOPS ML computational acceleration performance. The eXeL AI Kit design selected TensorFlow Lite as the framework for it's low resource requirements, especially suitable for low-power, low-memory, and mobile platform applications, yet very powerful for high-speed AI vision applications such as object detection and object classification. To make the eXeL AI Kit ™ suitable for our customers, especially those in the educational field, we leverage the resources from the Coral platform, and provide accessibility of online tutorials, including python examples and pre-compiled models, which have been easy to integrate with the Raspberry Pi host. We are proud to use the TensorFlow ecosystem in promoting AI/ML and increasing AI/ML accessibility, and we want to help continue optimizing the educational experience for our users, by increasing adoption and promoting more innovations.
More information on Coral from Google can be found at coral.ai