 However, their memory footprint, inference latency, and power consumption are prohibitive for many edgeprocessors, and it has been a challenge to deploy these models for edge applications and devices that have resource constraints .
<clarity>  However, their memory footprint, inference latency, and power consumption are prohibitive for many edgeprocessors, and it has been a challenge to deploy these models for edge applications and devices that have resource constraints .
 However, their memory footprint, inference latency, and power consumption are prohibitive for efficient inference at the edge, and even at the data center .