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“The Bitter Lesson” by Rich Sutton, 2019
This reading is a leading AI researcher's perspective on how the field of AI research oversteers toward "building in how we think we think we think" rather than relying on scaling computation. Can you think of counter examples where building in how we think that we think won't inhibit progress in the long run? What does the future of academic AI research look like if large, costly computational resources are required to make progress?
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