ARTIFICIAL INTELLIGENCE (AI) MODEL DEPENDENCY HANDLING IN HETEROGENEOUS COMPUTING PLATFORMS

Systems and methods for Artificial Intelligence (AI) model dependency handling in heterogenous computing platforms are described. In an illustrative, non-limiting embodiment, an Information Handling System (IHS) may include a heterogeneous computing platform comprising a plurality of devices and a memory coupled to the platform, where the memory includes a plurality of sets of firmware instructions that, upon execution by a respective device, enables the respective device to provide a corresponding firmware service, and where at least one of the devices operates as an orchestrator configured to: receive an indication of a relationship between a first AI model and a second AI model; and in response to an instruction to update the first AI model and in the absence of another instruction to update the second AI model, trigger installation of an update to the second AI model.