Google's Tensor chip narrative lost credibility as the open source community treats it as an irrelevance, forcing the company to defend a hardware strategy that developers have already bypassed.

Tensor chips perform well on their own benchmarks. The claim that Google made a bad chip is not what the community is saying. The claim is that Google made a chip nobody asked for. The open source AI hardware stack is defined by its portability: a model trained on NVIDIA can run on AMD; a workflow optimized for CUDA can be ported to ROCm; a LoRA fine-tuned on an RTX card deploys to a cloud TPU with minimal friction. Tensor demands the opposite — it requires XLA compilation and TensorFlow…

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What Google's Open Source Infrastructure Tells Us About the Future of AI

Google's investment in open-source infrastructure reveals a company betting on the ecosystem, not just its proprietary models. This shift in strategy redefines how the AI community thinks about Google's role in the open-source AI landscape.