Abstract: Apparatuses, systems, computer program products, and methods are disclosed for foundation model based fluid simulations. An apparatus includes a processor and a memory that stores code executable by the processor to receive a fluid foundation model that is pretrained on fluid data, deploy the received fluid foundation model into a downstream machine learning pipeline for a fluid dynamics application, reconfigure the fluid foundation model for the fluid dynamics application, and output results from the machine learning pipeline for the fluid dynamics application based on the reconfigured fluid foundation model.

Abstract: Apparatuses, systems, computer program products, and methods are disclosed for differentiable machines for physical systems. A hardware server device is configured to determine a plurality of differentiable models each representing a component of a physical system. A hardware server device is configured to combine a plurality of differentiable models using an integration layer so that the integration layer and the combined differentiable models form a differentiable machine representing a physical system. A hardware server device is configured to deploy a differentiable machine for an instance of a physical system.