fairseq    @fairseq    11/23/2021      

Mixture of experts training in fairseq is now 40% faster thanks to Microsoft's Tutel library! Blog: https://t.co/9x9zG9HpwU Fairseq code: https://t.co/lqZedr8HnT Tutel code: https://t.co/SMqbjaVeVB
  
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Alex Smola    @smolix    11/30/2021      

Trn1 training instances in preview today! @awscloud Thanks team!
  
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TheSequence    @TheSequenceAI    11/30/2021      

Mixture of experts is a deep learning model architecture that makes scaling easier. Recently, @MSFTResearch open-sourced Tutel. It's is a high-performance MoE library to facilitate the development of large-scale DNN models. Find it here: https://t.co/dnmIj9VDfU
  
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Google AI    @GoogleAI    11/17/2021      

Introducing RLiable, an easy-to-use library for reliably evaluating and reporting performance of #ReinforcementLearning algorithms, even when using only a handful of training runs. Learn more and access the library to build confidence in your results https://t.co/KnV61G5oBI
  
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TheSequence    @TheSequenceAI    11/30/2021      

Modern deep neural networks are large and require incredibly large training datasets. The traditional sequential approach is simply impractical. But we can use parallel training. The idea of parallelizable training is intuitive but incredibly hard to achieve. 1/2
  
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