[D] It’s 2026. Can we finally admit TensorFlow is the "COBOL of Machine Learning"?

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We keep telling students to learn both, but let’s look at the actual landscape: Research: 95%+ of HuggingFace and arXiv is PyTorch. Innovation: Even Google's own researchers are using JAX more than TF. DX: Debugging a custom layer in TF still feels like a fever dream compared to PyTorch’s native Pythonic flow. TF has the "legacy enterprise" crown, but for anything moving at the speed of SOTA, it’s not even a contest anymore. Is there any technical reason to start a greenfield project in TF to...