Why it's Super Hard to be an ML Researcher or Developer?

A few months ago, I came across this true story of a Harvard professor of political science, Gary King, who started working on the document clustering problem to give a Festschrift (a collection of writings published in honor of a scholar) to one of his colleagues, as the retirement gift. To do so, he asked his grad students to utilize every clustering algorithm ever invented. For those who know about this, clustering is a very old problem in the field of machine learning and statistics. Hence, there were plenty of methods available to apply in the literature, and they found around 250 algorithms. To compare the efficiency of all the algorithms, they coded an R package and what did they found?