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Data Science at Home


[RB] Replicating GPT-2, the most dangerous NLP model (with Aaron Gokaslan)

October 18, 2019

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In this episode, I am with Aaron Gokaslan, computer vision researcher, AI Resident at Facebook AI Research. Aaron is the author of OpenGPT-2, a parallel NLP model to the most discussed version that OpenAI decided not to release because too accurate to be published.
We discuss about image-to-image translation, the dangers of the GPT-2 model and the future of AI. Moreover, Aaron provides some very interesting links and demos that will blow your mind!

Enjoy the show! 
References

Multimodal image to image translation (not all mentioned in the podcast but recommended by Aaron)
Pix2Pix: 

https://phillipi.github.io/pix2pix/
 
CycleGAN:
https://junyanz.github.io/CycleGAN/
 
GANimorph
Paper: https://arxiv.org/abs/1808.04325
Code: https://github.com/brownvc/ganimorph
 
UNIT:https://arxiv.org/abs/1703.00848

MUNIT:https://github.com/NVlabs/MUNIT
DRIT: https://github.com/HsinYingLee/DRIT

 

GPT-2 and related 
Try OpenAI's GPT-2: https://talktotransformer.com/
Blogpost: https://blog.usejournal.com/opengpt-2-we-replicated-gpt-2-because-you-can-too-45e34e6d36dc
The Original Transformer Paper: https://arxiv.org/abs/1706.03762
Grover: The FakeNews generator and detector: https://rowanzellers.com/grover/