Research that demonstrates, say, 1000x reduction in power for training a known problem (ex: mnist) won't be considered irrelevant by the community. So is there

Research that demonstrates, say, 1000x reduction in power for training a known problem (ex: mnist) won't be considered irrelevant by the community. So is there a specific need to bias against large works apart from the carbon footprint argument? There remain questions to be answered in that space too - such as are current "neural" architectures adequate to cover the capabilities of the brain when upping only the scale? It was certainly worth knowing that scaling up was all that was required to compete with humans in DOTA. But will we hit wall as we near human level complexity? After all, the money spent on making movie which is "just" for entertainment trump's multi million $ deep learning experiments in costs which I guess have some correlation with the carbon footprint .. or the gases emitted in rocket launches. Do we really know whether this well intentioned call for green AI (which I right as hell want) will do too little for the greenness while biasing people against possible discoveries that can lead to a greener future a tad too early? Edit: pardon typos due to mobile device.