I think that's a fair argument, but from the quote above

> "Last March, AlphaGo, a program created by Google DeepMind, was able to beat a world-champion human player of Go, but only after it had trained on a database of thirty million moves, running on approximately a million watts. (Its opponent’s brain, by contrast, would have been about fifty thousand times more energy-thrifty, consuming twenty watts.)"

Let's say alphaGo trained for a year, that would be 1 MWyr energy consumed. And lets assume that Lee Se-dol's brain consumed 20W over 34 years of his live doing nothing but working on Go, that would be 640 Wyr, still a factor 1000-ish smaller.

Totally, I'm sure it's correct, and even if you were to bring the comparison in to line then the outcome is still "computer is watt hungry". The point is that the original statement, while correct, doesn't really say anything useful.

How would you know what amount of energy the human brain spent in learning to play Go, specifically? In the same time it was doing that, the human brain was also learning to do, and doing, a whole bunch of other things that AlphaGo was never even trained on- from moving limbs and controlling bodily functions to using language and recognising faces and so on. How would you isolate the amount of energy needed for training in Go, specifically?

I mean, in principle, if you had two numbers, "human energy consumption from learning Go" and "AlphaGo energy consumption from learning Go", you could compare them. But in practice there's no way to come up with such numbers, so what's the point of comparing apples and orangutans?

That's not really the point, more that it was originally not an apples to apples comparison and therefore doesn't really tell us anything. I have no doubt that the statement is correct, it's whether or not that statement has any meaning. As another comment pointed out, even if you compared the hours, the computer still uses a few orders of magnitude more energy for a more accurate (although completely theoretical) comparison.

AlphaGo took several months of self play on a large cluster, so training probably consumed many times more energy than a human in a lifetime.

The gain is in being able to clone the bot perfectly. Once trained you can make many of them. Also, if you look at what happened in Chess, the lessons learned from the large machines was absorbed and resulted in your smartphone now being able to outclass the human world champion.

You can expect a similar thing with Go at some point.

Same goes for the bot, then. A back of the envelope calculation suggest Lee's brain consumed as much energy in a 80 year lifetime as AlphaGo in half a day.

Not trying to say it isn't a correct statement, or that the outcome would be different if you lined everything up properly, only that the original statement doesn't really say anything meaningful.