There are many categories of information that defy easy systematic computational analysis. Patents are not one of them. Ever since the earliest litterae patentes were granted by host countries to foreigners willing to share their knowledge with their hosts, the monopoly rights granted by governments have been meticulously documented. The richness of data detailing both the monopoly right to exclude – granted to a patent’s owner – and the patent document’s informational disclosure of how to make and use a claimed invention – intended to enrich the metaphorical storehouse of knowledge – has accumulated at an accelerating pace since the days of the first letters patent. So rapidly has the information embodied in patents grown that analytical techniques for sorting and computationally evaluating that information have always lagged far behind the deluge of accumulating data. In lieu of precise algorithmic methods for understanding the contents of patents, a specialized guild of patent attorneys has evolved to sell their largely subjective interpretations of what patents disclose, cover, and are worth. Since patent attorneys must pass a challenging patent bar exam, in addition to a state bar exam, their numbers are controlled, allowing their fees to be high. However, recent years have seen the inexorable rise of more objective, falsifiable, mathematical, and computational methods for analyzing patents. Progress in patent analytics has accelerated rapidly in recent years, democratizing, elucidating, and making more rigorous the interpretation of patent data.