Makes Technology that Runs the TensorFlow® Machine-Learning Platform Easy to Implement and Deploy at an Ultra-Low Power Boulder, Colorado, June 21, 2019 (GLOBE NEWSWIRE) — SparkFun Electronics’ SparkX division, led by founder Nathan Seidle, has released the company’s first open-source, embedded-systems module—SparkFun Artemis, Engineering Version—to empower engineers, prototypers, and R&D teams to integrate the TensorFlow machine-learning platform into any design. Additionally, the team has launched three boards with the unshielded module: BlackBoard Artemis; BlackBoard Artemis Nano; and BlackBoard Artemis ATP. “Our goal is to enable anyone to integrate low-power machine learning into their designs and projects without being locked into a specific toolchain,” said SparkFun founder and engineer, Nathan Seidle, “The Artemis module is the first product to bridge the gap between hobbyists and consumer products, providing a single module from prototype to production.” Beyond its small size (15.5 x 10.5mm including antenna), key features of the ultra-low-power Artemis module include: “SparkFun has always been about making emerging technologies available to a wider audience—...