{"href":"https://api.simplecast.com/oembed?url=https%3A%2F%2Fstorygrid.simplecast.com%2Fepisodes%2Fart-automation-and-ai-part-2-3byINaA7","width":444,"version":"1.0","type":"rich","title":"Art, Automation, and AI — Part 2","thumbnail_width":300,"thumbnail_url":"https://image.simplecastcdn.com/images/b537903d-1878-44c5-a72d-c801bef00702/7f75a26e-1197-4e18-93e8-85e16c5f5fff/1453217557artwork.jpg","thumbnail_height":300,"provider_url":"https://simplecast.com","provider_name":"Simplecast","html":"","height":200,"description":"Can you do math on a sentence? Picking up from last week, Shawn Coyne argues that an LLM produces mimicked artifacts, not original ones, and that confusing the two is where the \"ghost in the machine\" fear comes from. Then he goes somewhere most writers won't like: writing can be evaluated objectively, all the way down to the sentence. Drawing on Gödel, Church, Turing, Deutsch, and Shannon, he explains why a finished piece of writing is a fully computable artifact, walks Tim Grahl through the exact process he uses to give feedback on a scene, and lays out what he's actually been working toward for 35 years: formalizing what he knows well enough that a machine can analyze a writer's work the way he would, and get them feedback in seconds instead of weeks."}