This week we discuss GPT-2, a new transformer-based language model from OpenAI that has everyone talking. It’s capable of generating incredibly realistic text, and the AI community has lots of concerns about potential malicious applications. We help you understand GPT-2 and we discuss ethical concerns, responsible release of AI research, and resources that we have found useful in learning about language models.

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Featuring:

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

Show Notes:

Relevant learning resources:

• Jay Alammar “Illustrated” blog articles:
  • The illustrated transformer
  • The illustrated BERT, elmo, and co
• Machine Learning Explained blog:
  • An In-Depth Tutorial to AllenNLP (From Basics to ELMo and BERT)
  • Paper Dissected: “BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding” Explained

References/notes:

• GPT-2 blog post from OpenAI
• GPT-2 Paper
• GPT-2 GitHub Repo
• GPT-2 PyTorch implementation
• Episode 22 of Practical AI about BERT
• OpenAI’s GPT-2: the model, the hype, and the controversy (towardsdatascience)
• The AI Text Generator That’s Too Dangerous to Make Public (Wired)
• Transformer paper
• Preparing for malicious uses of AI (OpenAI blog)

Something missing or broken? PRs welcome!