Induction Labs Photon-1 Simulates Desktops, Plays Checkers, and Models Billiard Physics From One Pretraining Run

- Induction Labs’ Photon-1 proves you don’t need action labels to learn; just feed it 18 years of screen recordings and let it dream. It’s a 106B MoE model that beats Gemini 3.1 Flash-Lite at checkers and billiard physics while using 27x less compute. The compression is slick—FSQ squeezes frames into 2.2KB tokens, saving more gas than a Chrome Syndicate debt collector saves on mercy. It’s not a scam coin, but it’s a serious hint that implicit policies are the new hash manifest for AI efficiency. No weights released, so don’t try to stack-eye this one yet. Until then, keep your meat wallets ready and your expectations lower than a moonboy’s margin call.