Edge-MultiAI: Multi-Tenancy of Latency-Sensitive Deep Learning Applications on Edge

Published in Proceedings of Utility Cloud Computing Conference, 2022, 2022

Recommended citation: SM Zobaed, Ali Mokhtari, Jaya Prakash Champati, Mathieu Kourouma, Mohsen Amini Salehi (2022). "Edge-MultiAI: Multi-Tenancy of Latency-Sensitive Deep Learning Applications on Edge." Utility Cloud Computing Conference. https://arxiv.org/abs/2211.07130

Offering people rewards and incentives typically improves their performance on skilled motor tasks. However, the mechanisms by which motivation impacts motor skills remains unclear. In two experiments, we show that motivation impacts motor sequencing skills in two separate ways. First, the prospect of reward speeds up the execution of all actions. Second, rewards provide an additional boost to motor planning when explicit skill knowledge can be used to prepare movements in advance.