A retrospective of a distributed edge-ML project whose big-bang integration yielded six of forty expected minutes of functionality, attributing the failure to late integration, weak communication, and psychological bias, and recommending mock-based early deployment and top-down planning.
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Lessons from a Big-Bang Integration: Challenges in Edge Computing and Machine Learning
A retrospective of a distributed edge-ML project whose big-bang integration yielded six of forty expected minutes of functionality, attributing the failure to late integration, weak communication, and psychological bias, and recommending mock-based early deployment and top-down planning.