The Staggering Cost of Training SOTA AI Models

Synced recently reported on XLNet, a new language model developed by CMU and Google Research which outperforms the previous SOTA model BERT (Bidirectional Encoder Representations from Transformers) on 20 language tasks including SQuAD, GLUE, and RACE; and has achieved SOTA results on 18 of these tasks.

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