Researchers From NVIDIA, Stanford University and Microsoft Research Propose Efficient Trillion-Parameter Language Model Training on GPU Clusters | MarkTechPost

Researchers From NVIDIA, Stanford University and Microsoft Research Propose Efficient Trillion-Parameter Language Model Training on GPU Clusters. — Lees op www.marktechpost.com/2021/04/19/researchers-from-nvidia-stanford-university-and-microsoft-research-propose-efficient-trillion-parameter-language-model-training-on-gpu-clusters/

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[2104.06644] Masked Language Modeling and the Distributional Hypothesis: Order Word Matters Pre-training for Little

A possible explanation for the impressive performance of masked language model (MLM) pre-training is that such models have learned to represent the syntactic structures prevalent in classical NLP pipelines. In this paper, we propose a different explanation: MLMs succeed on downstream tasks almost entirely due to their ability to model Read more

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NVIDIA Announces Technology For Training Giant Artificial Intelligence Models

Senior Analyst AI and Quantum Computing Paul Smith-Goodson discusses NVIDIA GTC, the premier annual conference for developers, scientists, and businesses interested in machine learning or AI. He dives into one of Huang’s most exciting announcements of a newly designed AI platform — Lees op www.forbes.com/sites/moorinsights/2021/04/12/nvidia-announces-technology-for-training-giant-artificial-intelligence-models/

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