• Google launched TorchTPU on Tuesday, following Amazon's TorchNeuron release Monday, to simplify migration of PyTorch applications to their proprietary AI chips.
• Lower switching costs could shift workloads away from Nvidia, weakening its pricing power while reducing cloud providers' dependence on its hardware.
• Amazon is submitting changes to PyTorch to reduce Nvidia-specific dependencies, potentially broadening support for competing chip architectures.
• Adoption will depend on performance, reliability and operating costs; Nvidia's established software ecosystem remains a competitive advantage.

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