> You should familiarize yourself with power law processes... Since you brought it up: my PhD was in applied probability, and I work with heavy-tailed natural

> You should familiarize yourself with power law processes... Since you brought it up: my PhD was in applied probability, and I work with heavy-tailed natural data every weekday. * As my comment noted, ML literally says 170K or maybe 175K, and flat-out dismisses 220K. The latter is an interesting figure, because we recently surpassed it. We're now well out of the 170-175K envelope and still rising at about 5K deaths per week, about 20K deaths per month [1]. Note that our weekly death toll is the implied accuracy of ML's prediction. This is a failure. If ML thought there was a power law behind the mortality from an in-process event, he should have said "170K deaths or maybe 1.7M". But he didn't say that, did he? * It's interesting to see an interview with an excellent science communicator. They will say what we know, and not a bit more than that. They will choose their words carefully. They will distinguish between speculation and accepted truth. I live in southern CA, and Lucy Jones (formerly of the USGS) is such a person, for earthquakes. These people are a treasure, because this stuff is hard and it's important to get it right if you're going to make public statements. [1] https://www.cdc.gov/coronavirus/2019-ncov/covid-data/forecasting-us.html https://www.cdc.gov/coronavirus/2019-ncov/covid-data/forecas...