Daniel Jeffries, the Chief Technical Evangelist at Pachyderm, describes how consolidation around a canonical software or hardware stack can accelerate the adoption of new technologies. He suggests that a canonical software stack for machine learning is emerging, centered on tools for 1) data gathering and transformation; 2) experimentation, training, tuning, and testing; 3) productionization, deployment and inference; and 4) monitoring, auditing, management, and retraining. He categorizes popular ML tools and platforms according to this taxonomy.