EPISODE · Oct 18, 2019 · 37 MIN
[RB] Replicating GPT-2, the most dangerous NLP model (with Aaron Gokaslan) (Ep. 83)
from Data Science at Home · host Francesco <frag> Gadaleta
Join the discussion on our Discord server 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! ReferencesMultimodal 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/ GANimorphPaper: https://arxiv.org/abs/1808.04325Code: https://github.com/brownvc/ganimorph UNIT:https://arxiv.org/abs/1703.00848MUNIT:https://github.com/NVlabs/MUNITDRIT: 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-45e34e6d36dcThe Original Transformer Paper: https://arxiv.org/abs/1706.03762Grover: The FakeNews generator and detector: https://rowanzellers.com/grover/ This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit datascienceathome.substack.com
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[RB] Replicating GPT-2, the most dangerous NLP model (with Aaron Gokaslan) (Ep. 83)
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