A new kind of large language model, developed by researchers at the Allen Institute for AI (Ai2), makes it possible to control how training data is used even after a model has been built. Once data is baked into an AI model today, extracting it from that model is a bit like trying to recover the eggs from a finished cake. “Conventionally, your data is either in or out,” says Ali Farhadi, CEO of Ai2, based in Seattle, Washington. And you have no way out, unless you force me to go through another multi-million-dollar round of training.”Ai2’s avant-garde approach divides up training so that data owners can exert control. And because of how the data owner’s model is merged with the final one, it is possible to extract the data later on.