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> because they can work end-2-end Agree. Not just end-2-end, but the same model can be applied to many different tasks. DeepMind's recent papers make progress
by backpropaganda 9y ago
> because they can work end-2-end
Agree. Not just end-2-end, but the same model can be applied to many different tasks. DeepMind's recent papers make progress in image generation, audio generation, language modeling & machine translation using the same basic construct of a masked dilated shifted convolutions.