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Democratizing ML for speech

Practical AI

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Balancing Openness and Proprietary Innovation in Machine Learning

This chapter explores the challenges organizations encounter in choosing between public accessibility and proprietary control of their machine learning projects. It emphasizes the need for ongoing dataset maintenance and the role of legal and business experts in making these decisions.

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