While Python is an interpreted language, many AI frameworks use underlying C/C++ or CUDA implementations for computationally intensive tasks. This hybrid approach ensures frameworks can handle large datasets and complex models efficiently, enabling scalable backend solutions without sacrificing performance.

While Python is an interpreted language, many AI frameworks use underlying C/C++ or CUDA implementations for computationally intensive tasks. This hybrid approach ensures frameworks can handle large datasets and complex models efficiently, enabling scalable backend solutions without sacrificing performance.

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