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Deep learning is driving rapid innovations in artificial intelligence and influencing massive disruptions across all markets. However, leveraging the promise of deep learning today is extremely challenging. The explosion of deep learning frameworks is adding complexity and introducing steep learning curves. Scaling out over distributed hardware requires specialization and significant manual work; and even with the combination of time and resources, achieving success requires tedious fiddling and experimenting with parameters.