The participants were to break into teams, build a drone, implement machine learning techniques, gather and analyze data via Iron, and maneuver their drone across multiple courses. The teams that finished the courses and displayed the most innovative technical solutions were crowned champion.
The ability to utilize GPU instances and fire up containers that run libraries like Keras and TensorFlow allows for the offloading of heavy computational workloads even in highly dynamic environments. In the last few months, we’ve been speaking to more and more customers who are using Iron for large ML and AI workloads, often breaking them into distinct types of work units that require different levels of GPU, CPU and memory requirements.
Congratulations to the winners of the contest and all those that participated! It looked incredibly challenging. If you have any questions about utilizing GPU’s, machine learning, artificial intelligence, or any other computational heavy lifting jobs using Iron, feel free to contact us at email@example.com as we’ll be happy to chat.