Four short links: 6 June 2019

Software Engineering for Machine Learning, Generalizations in Learning, Computer Dance, and Firefighting in Product Development

By Nat Torkington
June 6, 2019
Four Short Links
  1. Software Engineering for Machine Learning (Microsoft Research) — We collected some best practices from Microsoft teams to address [several essential engineering challenges that organizations may face in creating large-scale AI solutions for the marketplace]. In addition, we have identified three aspects of the AI domain that make it fundamentally different from prior software application domains: 1) discovering, managing, and versioning the data needed for machine learning applications is much more complex and difficult than other types of software engineering, 2) model customization and model reuse require very different skills than are typically found in software teams, and 3) AI components are more difficult to handle as distinct modules than traditional software components—models may be “entangled” in complex ways and experience non-monotonic error behavior.
  2. Open Long-Tailed Recognition (Berkeley) — A practical system shall be able to classify among a few common and many rare categories, to generalize the concept of a single category from only a few known instances, and to acknowledge novelty upon an instance of a never seen category. We define OLTR as learning from long-tail and open-end distributed data and evaluating the classification accuracy over a balanced test set which includes head, tail, and open classes in a continuous spectrum.
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  4. Hype Cycle: Machine Learning (Vimeo) — dance being changed by computers.
  5. Past the Tipping Point: The Persistence of Firefighting in Product DevelopmentIn this paper, we try to answer three questions: (1) why does firefighting exist, (2) why does firefighting persist, and (3) what can managers do about it? The most important result of our studies is that product development systems have a tipping point. In models of infectious diseases, the tipping point represents the threshold of infectivity and susceptibility beyond which a disease becomes an epidemic. Similarly, in product development systems there exists a threshold for problem-solving activity that, when crossed, causes firefighting to spread rapidly from a few isolated projects to the entire development system. Our analysis also shows that the location of the tipping point, and therefore the susceptibility of the system to the firefighting phenomenon, is determined by resource utilization in steady state.
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