This invention describes a system for making neural networks more efficient by using pre-defined, multi-layered building blocks called "macro layers." It works by having a graphics processing unit (GPU) define these blocks, adapt them to the network's specific data, and then train the network using these optimized structures. The claims specifically narrow the invention to this process happening within the specialized hardware of a GPU.
Why it matters: The explosion of large, complex neural networks since 2021 makes hardware-level optimization for modular structures like macro layers far more critical for efficient training and deployment. Specialized AI hardware development has accelerated, making this architectural approach more timely.
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