It's a good post. If you're interested, Nassim Taleb (shudders) wrote a counterpoint for Edge.org that seems to have disappeared. It exists on the Internet Arch

It's a good post. If you're interested, Nassim Taleb (shudders) wrote a counterpoint for Edge.org that seems to have disappeared. It exists on the Internet Archive, though: https://web.archive.org/web/20140606195420/http://edge.org/response-detail/25401 https://web.archive.org/web/20140606195420/http://edge.org/r... Well, that's not quite accurate -- Taleb doesn't argue that we should do away with squared error, he says we should do away with the standard deviation in favour of expected deviation from the mean. (Hrm, I'm going back and forth on whether there's a substantive difference between the concepts of variance/standard deviation as measures of a probability distribution and squared/RMS error measures... Obviously they coincide when the "prediction" is the mean of the data, but I don't think that's terribly convincing. I think it'd be perfectly reasonable to use squared error in your model fit and parametrise your Gaussian distributions by their average absolute deviation from the mean.) Discussed on HN https://news.ycombinator.com/item?id=7064435 https://news.ycombinator.com/item?id=7064435