{"href":"https://api.simplecast.com/oembed?url=https%3A%2F%2Fstorygrid.simplecast.com%2Fepisodes%2Fart-automation-and-ai-part-3-55QpPH2c","width":444,"version":"1.0","type":"rich","title":"Art, Automation, and AI — Part 3","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":"<iframe src=\"https://player.simplecast.com/ba51a221-c443-46ce-8b3f-882a23078afd\" height=\"200\" width=\"100%\" title=\"Art, Automation, and AI — Part 3\" frameborder=\"0\" scrolling=\"no\"></iframe>","height":200,"description":"In Part 3 of Art, Automation, and AI, Tim Grahl and Shawn Coyne ask what it means that language can be turned into math. Shawn compares a developmental editor to a CPA who reads only the evidence and always tells the truth, and explains the difference between an LLM’s probability inferences and a deterministic calculation. Tim lays out why writing is one of the most wicked learning environments there is, and why knowledge never turns into skill without fast, accurate feedback. Shawn then describes the software he built: a calculator, not an AI, that grades a writer’s sentences against 35 years of editorial judgment and returns feedback within 24 hours."}