Scott Alexander shows how he won his 2022 bet about AI image generation capabilities, tracking the progress from early failures to complete success in 2025, using this to argue against AI skeptics. Longer summary

Scott Alexander describes the resolution of a bet he made in June 2022 about AI image generation capabilities. The bet claimed that by June 2025, AI would master image compositionality and be able to accurately generate specific complex scenes. The post shows the progression of AI image generation from 2022 to 2025, starting with early failures by DALL-E2, through various partial successes with Google Imagen and DALL-E3, and ending with ChatGPT 4o's complete success in May-June 2025. Scott uses this to argue against critics who claimed AI was just a 'stochastic parrot' that couldn't achieve true understanding, though he acknowledges some remaining limitations with very complex prompts. Shorter summary

Scott analyzes how technology can make previously profound experiences feel cheap and commonplace, using examples from medieval art to AI-generated images, while suggesting that maintaining wonder is still possible through individual effort. Longer summary

Scott explores the concept of semantic apocalypse - how technological progress can cheapen previously profound experiences - through three connected narratives. He starts with the medieval use of ultramarine blue for painting the Virgin Mary's coat, then discusses Erik Hoel's concerns about AI art cheapening Studio Ghibli's work, and finally examines this pattern throughout history. The post suggests that while this loss of wonder is real, it might be more about personal perception than technology itself, citing Chesterton's and Blake's ability to maintain wonder despite familiarity. The piece concludes that maintaining childlike wonder is possible and valuable, even in an age of abundant AI-generated art. Shorter summary

Scott presents results from his AI art Turing test showing most people struggled to distinguish AI from human art, with professionals doing slightly better and participants unexpectedly preferring AI art. Longer summary

Scott analyzes the results of his AI art Turing test where 11,000 people tried to distinguish between human and AI-generated art. The median score was 60%, only slightly above chance, showing most people had difficulty identifying AI art. Participants tended to judge images based on style rather than subtle quality differences, incorrectly assuming traditional styles were human and digital art was AI. Interestingly, people slightly preferred AI art even when they claimed to hate it. However, professional artists and AI critics scored better at detection, suggesting they may notice subtle flaws that others miss. Shorter summary

Scott Alexander announces an AI Art Turing Test with a link to a form, closing on 10/21, with results to be posted the following week. Longer summary

Scott Alexander announces an AI Art Turing Test, providing a link to a form that readers can complete. The test is expected to take about 20 minutes, and the form will close on Monday 10/21. Scott plans to post the results the following week. He mentions that an answer key will be provided in the comments of the post, with a more detailed version including attributions in the results post. Scott advises readers not to read the comments until they've completed the test. Shorter summary

Scott Alexander experiments with DALL-E 2 to create stained glass window designs, exploring the AI's capabilities and limitations in interpreting complex prompts. Longer summary

Scott Alexander explores the challenges and quirks of using DALL-E 2, an AI art generator, to create stained glass window designs depicting the Virtues of Rationality. He details his attempts to generate images for different virtues, discussing the AI's strengths, limitations, and unexpected behaviors. The post analyzes how DALL-E interprets prompts, handles historical figures and concepts, and struggles with combining specific subjects and styles. Scott concludes that while DALL-E is capable of impressive work, it currently has difficulties with unusual requests and maintaining consistent styles across multiple images. Shorter summary