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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/
[RB] Replicating GPT-2, the most dangerous NLP model (with Aaron Gokaslan) (Ep. 83)