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title: Scaling AI/ML Infrastructure at Uber | daily.dev
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# Scaling AI/ML Infrastructure at Uber

**[Uber Engineering](https://daily.dev/sources/uber)** · 8 min read · 4 upvotes · 0 comments

## Summary

Uber has made significant progress in scaling their AI/ML infrastructure, transitioning from on-prem to cloud infrastructure and optimizing existing infrastructure. They have implemented a unified federation layer for batch workloads, upgraded network bandwidth for training efficiency, and upgraded memory to improve GPU allocation rates. They are also building new infrastructure by evaluating price-performance ratios of cloud SKUs and improving LLM training efficiency through memory offload.

## Full article

daily.dev links to this article rather than hosting it. Read it at the original source: <https://www.uber.com/blog/scaling-ai-ml-infrastructure-at-uber/>

---

Tags: [#cloud](https://daily.dev/tags/cloud), [#machine-learning](https://daily.dev/tags/machine-learning), [#gpu](https://daily.dev/tags/gpu), [#uber](https://daily.dev/tags/uber)

[View this post on daily.dev](https://daily.dev/posts/scaling-ai-ml-infrastructure-at-uber-rdn0prjic)

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