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Machine learning models are getting larger and larger — some might even say, humongous. The world’s most advanced technology companies have been in an arms race to see who can train the largest model (MUM, OPT, GPT-3, Megatron), while other companies focused on production systems have scaled their existing models to great effect. Through all the excitement, what’s gone unsaid is the myriad of practical challenges larger models present for existing AI infrastructure and developer workflows.