Task: Language Identification
Input (Spanish, English): A few issues with this paper: 1- I find finding #2 trivial and unworthy of mention, but the author don't seem to agree with me that it is. See discussions. 2- Finding #1 relies on Fig #4, which appears very noisy and doesn't provide any error analysis. It makes me question how robust this finding is. One would have naively expected the power usage trend to mirror Fig #3, but given the level of noise, I can't convince myself whether the null hypothesis of there being no dependency between batch size and power consumption is more likely than the alternative. 3- Paper is unfriendly to colorblind readers (or those with B/W printers)  Overall, this paper is a reasonable review of where we are in terms of SOTA vision architectures, but doesn't provide much new insight. I found most interesting the clear illustration that VGG models stand out in terms of being a bad tradeoff in resource-constrained environments (too many researchers are tempted to benchmark their model compression algorithm on VGG-class models because that's always where one can show 10x improvements without doing much.)
Output (English): en