A new model, the Differential Transformer, addresses inefficiencies in the popular transformer architecture by filtering irrelevant context and amplifying needed signal. This innovation has beneficial implications for long-context language modeling, hallucination mitigation, and in-context learning, promising to improve the performance of AI systems across numerous industry applications.