Generative Pre-trained Transformer (GPT)

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• Case Studies
  • Writing
  • Publishing
• Text Transfer Learning
• Natural Language Generation (NLG)
• Generated Image
• Attention Mechanism/Transformer Model
• OpenAI Blog | OpenAI
• Language Models are Unsupervised Multitask Learners | Alec Radford, Jeffrey Wu, Rewon Child, David Luan, Dario Amodei, and Ilya Sutskever
• Neural Monkey | Jindřich Libovický, Jindřich Helcl, Tomáš Musil Byte Pair Encoding (BPE) enables NMT model translation on open-vocabulary by encoding rare and unknown words as sequences of subword units.

• Bidirectional Encoder Representations from Transformers (BERT)
• ELMo
• Language Models are Unsupervised Multitask Learners - GitHub
• Microsoft Releases DialogGPT AI Conversation Model | Anthony Alford - InfoQ - trained on over 147M dialogs

GPT-3

• Language Models are Few-Shot Learners | T. Brown, B. Mann, N. Ryder, M. Subbiah, J. Kaplan, P. Dhariwal, A. Neelakantan, P. Shyam, G. Sastry, A. Askell, S. Agarwal, A. Herbert-Voss, G. Krueger, T. Henighan, R. Child, A. Ramesh, D. Ziegler, J. Wu, C. Winter, C. Hesse, M. Chen, E. Sigler, M. Litwin, S. Gray, B. Chess, J. Clark, C. Berner, S. McCandlish, A. Radford, I. Sutskever, and D. Amodei - arXiv.org
• OpenAI API ...today the API runs models with weights from the GPT-3 family with many speed and throughput improvements.
• GPT-3 by OpenAI – Outlook and Examples | Praveen Govindaraj | Medium

Why did OpenAI choose to release an API instead of open-sourcing the models? There are three main reasons we did this.

1. First, commercializing the technology helps us pay for our ongoing AI research, safety, and policy efforts.
2. Second, many of the models underlying the API are very large, taking a lot of expertise to develop and deploy and making them very expensive to run. This makes it hard for anyone except larger companies to benefit from the underlying technology. We’re hopeful that the API will make powerful AI systems more accessible to smaller businesses and organizations.
3. Third, the API model allows us to more easily respond to misuse of the technology. Since it is hard to predict the downstream use cases of our models, it feels inherently safer to release them via an API and broaden access over time, rather than release an open source model where access cannot be adjusted if it turns out to have harmful applications.

GPT-2

• (117M parameter) version of GPT-2 | GitHub
• How to Get Started with OpenAIs GPT-2 for Text Generation | Amal Nair - Analytics India Magazine
• GPT-2: It learned on the Internet | Janelle Shane
• Too powerful NLP model (GPT-2): What is Generative Pre-Training | Edward Ma
• GPT-2 A nascent transfer learning method that could eliminate supervised learning some NLP tasks | Ajit Rajasekharan - Medium
• OpenAI Creates Platform for Generating Fake News. Wonderful | Nick Kolakowski - Dice

a text-generating bot based on a model with 1.5 billion parameters. ...Ultimately, OpenAI's researchers kept the full thing to themselves, only releasing a pared-down 117 million parameter version of the model (which we have dubbed "GPT-2 Junior") as a safer demonstration of what the full GPT-2 model could do.Twenty minutes into the future with OpenAI’s Deep Fake Text AI | Sean Gallagher

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• Try GPT-2...Talk to Transformer - completes your text. | Adam D King, Hugging Face and OpenAI

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r/SubSimulator

Subreddit populated entirely by AI personifications of other subreddits -- all posts and comments are generated automatically using:

• Markov Chain Model
• GPT-2 Language

results in coherent and realistic simulated content.

GetBadNews

• Get Bad News game - Can you beat my score? Play the fake news game! Drop all pretense of ethics and choose the path that builds your persona as an unscrupulous media magnate. Your task is to get as many followers as you can while