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I am not sure calling bullshit on images works the same way, given we generally want to invite creativity to image generation. Although an adversarial extra-fi
by Nevermark 4y ago
I am not sure calling bullshit on images works the same way, given we generally want to invite creativity to image generation.
Although an adversarial extra-finger detector seems in order! Extra fingers are not creativity. They are taboo!!
But for text, there is a lot of structure around bullshitting, and fortunately, the internet is full of examples of people calling bullshit. As long as the bullshit adversary has to give a strong critique to back up any bullshit call, it should work.
And bullshit judgments can be de-bullshitted too.
This would be the same as what our social circles, work colleagues, families, etc. do for us, so a circular firing squad of bullshit judges, who also give gold stars for quality responses, seems like a natural solution for models too.
- not2b 4y agoThe first really good image generators for faces (see for example https://this-person-does-not-exist.com https://this-person-does-not-exist.com ) used GANs, which were trained by having one model generate faces and another model saying bullshit, that isn't a face. I'm not worried about using approaches like this to converge on truth (model A generates an answer to a question, model B attempts to refute model A). Perhaps we could train model A to generate lies that model B can't detect.