Is ML Clustering a Good Addition to Human Driven Taxonomy?

David Mard: I find ML clustering algorithms to be useful adjunct to human driven tax and taxonomy tax on no no make categories. He says the differences in data science, usually you have aliases and in software engineering, you have what's called all labels. An all label would be AWS. And that helps with findability and discovery and information retrieval for humans and machines. Two separate tasks, human information retrieval and then machine.