Probably one of the few people that read the whole thing, but the argument is, in my opinion, pretty weak. It basically boils down to making some kind of equivalence between metaphysics and pure mathematics. Of course, it ignores the main force of mathematical progress: theorem-building. Metaphysics might be "interconnected in much the same way" as Dr. Baron argues, but let's not kid ourselves. To argue that metaphysics is as "conceptually interrelated" as mathematics is is a real stretch. Just consider volume: it's estimated that around <i>a quarter of a million</i> theorems are proved every year. That's real, measurable, progress; what's the metaphysics equivalent?<p>The distinction between "internally applied metaphysics" and "externally applied metaphysics" on page 14 is a shameless red herring. The <i>only</i> thing we ought to care about, given the preceding section on applications of pure mathematics is "externally applied metaphysics," but in typical philosopher fashion, Dr. Baron equivocates for a few unnecessary pages. Finally, let me leave you with this gem: "All three cases are examples in which scientists appear to be doing metaphysics. Computer scientists build models of objects and categories in order to provide the resources for artificial intelligence to successfully navigate the world, or make judgements [sic] about it." Yeah, that's not metaphysics; it's pretty much just regular taxonomy (and, by the way, the term of art is <i>labeling</i>). TensorFlow models have nothing to do with metaphysical models, and this is exactly why philosophers get such a bad rap. They extend far beyond the reaches of their knowledge base and don't even have the courtesy to look up "machine learning model" on Wikipedia.