The papers I provided go a bit beyond "electrical usage". One of them is cited by the paper in question. Yes, they are approximations in lieu of more accurate

The papers I provided go a bit beyond "electrical usage". One of them is cited by the paper in question. Yes, they are approximations in lieu of more accurate data but that doesn't invalidate them as a tool or a motivation for future work such as this one. Consider further that it's not just OpenAI's models in question: it's every practitioner who attempts to train similarly large models. These practitioners may not be using "green" data centers, even if we generously assume that OpenAI does. (Microsoft's 100% renewable target for data centers isn't until 2025. Read another way: they may be trying but they're not there yet.) The available data and approximations illustrate that it is not accurate to assume that the average data center are powered by 100% renewables and carbon neutral. Thus the only reasonable conclusion is that more efficient models will have a positive impact on CO2 which is the motivation of the paper. Even if you don't agree, it's not completely unfounded and is based on at least some research and data. At the end of the day, is this really worth fighting against? Who wants less energy efficient models?