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Abstract:

This presentation zooms in on the problem of defining open source machine learning and whether reasoning about it in the framework of intellectual property rights makes sense. It explains why a uniform definition of open source machine learning under the stewardship of the Open Source Initiative is key for understanding how existing open source licensing models could be applied to machine learning. We discuss how the way we define open source machine learning and the objectives pursued with such a definition play an essential role in shaping future licensing and business models.