Uber is expanding its use of AWS-designed chips, including Graviton and Trainium, to run AI workloads more efficiently across its platform. The shift reflects a broader move among enterprises to control rising cloud costs as AI systems scale. By tuning workloads for custom silicon, Uber aims to balance performance and spending, even as this approach introduces new complexity in managing cloud infrastructure.
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