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BERT: one NLP model to rule them all
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Daniel Whitenack and Chris Benson

· 39 Minutes

PodcastPractical AI

BERT: one NLP model to rule them all

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Fully Connected – a series where Chris and Daniel keep you up to date with everything that’s happening in the AI community.

This week we discuss BERT, a new method of pre-training language representations from Google for natural language processing (NLP) tasks. Then we tackle Facebook’s Horizon, the first open source reinforcement learning platform for large-scale products and services. We also address synthetic data, and suggest a few learning resources.

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Featuring:

  • Chris Benson – Website, GitHub, LinkedIn, X
  • Daniel Whitenack – Website, GitHub, X

Show Notes:

News/Discussion:

  • Is artificial intelligence set to become art’s next medium?
  • BERT (a new method for obtaining rich contextual language representations during pre-training): 
    • Google research article
    • TensorFlow BERT
    • BERT paper
    • PyTorch BERT
    • NY Times article
    • Example Colab notebook
    • BERT explained article
    • Transformer paper
    • Google Open Sources BERT to Train Natural Language Models Without Breaking the Bank
  • Horizon: The first open source reinforcement learning platform for large-scale products and services
  • Does Synthetic Data Hold The Secret To Artificial Intelligence?
  • AI Experts: Moving forward with AI likely a series of small steps, not giant leaps

Learning resources:

  • The Backpropagation Algorithm Demystified

Books

  • “Grokking Deep Learning” by Andrew Trask

Upcoming Events: 

  • Register for upcoming webinars here!

Original source

This story was published by Practical AI and written by Daniel Whitenack and Chris Benson. SyncAI.news shows a preview; the complete article is on the publisher's site.

Read the full story on share.transistor.fm

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