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Uber taps Amazon chips to boost AI

Uber is expanding its AWS contract to run more ride-sharing features on Amazon’s Graviton chips and will test Trainium3 for AI workloads, Amazon said on April 7.

The move adds AWS to Uber’s large cloud relationships after the company signed multiyear deals with Oracle and Google in 2023 to shift most of its IT infrastructure from its own data centers.

Uber has been moving toward more efficient computing architectures, including Arm-based systems.

🔗 Source: TechCrunch

🧠 Food for thought

Implications, context, and why it matters.

Uber already did the work for Arm adoption

  • Uber’s latest shift builds on a seven-year move off its own data centers 1.
  • During the 2023 move to Oracle Cloud Infrastructure (OCI), Oracle’s cloud computing platform, and Google Cloud Platform, Google’s cloud computing platform, Uber added support for Arm-based Ampere processors, server chips built on Arm’s energy-efficient architecture, to cut costs and improve efficiency 2.
  • That effort rebuilt the build pipeline for more than 5,000 software services, which lowers the effort needed to adopt another Arm-based chip such as AWS Graviton 2.

Uber’s Trainium test aims to cut AI costs

  • Uber is testing Amazon’s Trainium3 AI chip as part of its push to reduce spending on large-scale AI workloads.
  • AWS pitches its custom Trainium chips as delivering up to 50% lower training costs than graphics processing units (GPUs) for some workloads, including models with more than 100 billion parameters 3.
  • Uber keeps Google Cloud and Oracle Cloud Infrastructure (OCI) in rotation while it tests Trainium3 1.
  • With multiple providers, Uber can compare performance and seek better pricing, which pressures NVIDIA’s pricing leverage; AWS and some third-party analysis argue Trainium can run cheaper in some cost comparisons 4.

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