👉 Specify computing is an approach to optimizing the performance of machine learning models by explicitly defining and controlling the computational resources required for training and inference. Unlike traditional autoML methods that often rely on heuristic search strategies to find optimal configurations, specify computing uses a structured process where developers and engineers specify the exact computational resources needed, such as CPU cores, GPU units, memory, and network bandwidth. This allows for more precise resource allocation, leading to significant improvements in efficiency, cost-effectiveness, and the ability to scale models to meet specific demands. By providing a clear blueprint of resource requirements, specify computing enables better management of computational budgets and facilitates the deployment of models in production environments with greater reliability and performance predictability.
