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"GPT-3 was trained on is so large that the model contains a certain fraction of the actual complexity of the world. But how much is actually inside these models, implicitly embedded within these neural networks?
I decided to test this and see if I could examine the GPT-3 model of the world through the use of counterfactuals. Specifically, I wanted to see if GPT-3 could productively unspool histories of the world if things were slightly different, such as if the outcome of a war were different or a historical figure hadn’t been born. I wanted to see how well it could write alternate histories." - Samuel Arbesman
From Cabinet of Wonders newsletter by Samuel Arbesman
Great tweet thread summarizing his post
"Securities" podcast is produced and edited by Chris Gates
No transcript available for this episode.