Yeah, these AI companies have some weird paradox that if they actually had a model that was super efficient and could arbitrage cost/intelligence of other inferior models, they would keep everything about it secret. If an intelligence research group had something groundbreaking, they would just dump their own money into the magic money machine.

Instead, to make up for the lack of economic viability of their models, they are forced to release publicly to get marketing to get others to pay based on hype.

If everyone else can spin up their own version of your product in under a month, there probably wasn't much product there.

> Our post-training utilizes label-smoothed cross-entropy for valid schema outputs paired with a Brier loss to refine probability calibration.