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Chaos and Pain in Machine Learning, and the ‘DevOps for ML Manifesto'

Most AI/ML projects start shipping models into production, where they can deliver business value, using the no-process process. That is, people just do their best by creating an ad-hoc process with familiar tools. This works for tiny teams at first, but as the team grows you'll discover significant chaos and pain trying to operationalize AI.