 While the accuracy and computational performance is still a limiting factor for the direct use of PINN for solving , hybrid strategies are a viable option for the development of a new class of linear solvers combining emerging deep-learning and traditional scientific computing approaches .
<clarity>  While the accuracy and computational performance is still a limiting factor for the direct use of PINN for solving , hybrid strategies are a viable option for the development of a new class of linear solvers combining emerging deep-learning and traditional scientific computing approaches .
 While the accuracy and computational performance is still a limiting factor for the direct use of PINN for solving , hybrid strategies combining old traditional linear solver approaches with new emerging deep-learning techniques are among the most promising methods for developing a new class of linear solvers combining emerging deep-learning and traditional scientific computing approaches .