I agree. Using watts, which are energy (joules) per unit time (second), to measure the energy consumption of training a model is the wrong unit to begin with.
One cannot measure the total energy consumption of something without knowing both the wattage and the time spent running at that voltage. While training a neural network is often done from scratch or a pre-trained model with a known training time, the brain of a human being does not start developing from zero their birth. Measuring the amount of energy spent on a specific human being trained on a task would also have to account for the billions of years of evolution that lead up to the present-day structure of the human brain. It would be very hard but also very interesting to approximate the energy spent on this, but it may not be relevant to machine learning as the processing power scales and time periods are completely different than those involved in the development of the human brain.
One cannot measure the total energy consumption of something without knowing both the wattage and the time spent running at that voltage. While training a neural network is often done from scratch or a pre-trained model with a known training time, the brain of a human being does not start developing from zero their birth. Measuring the amount of energy spent on a specific human being trained on a task would also have to account for the billions of years of evolution that lead up to the present-day structure of the human brain. It would be very hard but also very interesting to approximate the energy spent on this, but it may not be relevant to machine learning as the processing power scales and time periods are completely different than those involved in the development of the human brain.