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blog: remove filler word from kubecon-eu-2026 recap #318

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2 changes: 1 addition & 1 deletion blog/kubecon-eu-2026-recap/index.md
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Expand Up @@ -75,7 +75,7 @@ This is why what appears to be a low-level problem has become one of the core is

HAMi Maintainer Xiao Zhang's talk started from a classic, long-standing problem in the Kubernetes community: **How can multiple containers share a GPU?**

While this question seems specific, it actually points to a challenge the entire AI infrastructure ecosystem faces. Once you enter inference, batch processing, online serving, and multi-tenant mixed scenarios, GPUs can no longer be simply allocated in an "exclusive whole-card" manner.
While this question seems specific, it actually points to a challenge the entire AI infrastructure ecosystem faces. Once you enter inference, batch processing, online serving, and multi-tenant mixed scenarios, GPUs can no longer be allocated in an "exclusive whole-card" manner.

The significance of this talk lies in putting HAMi's solution back into the original context of the Kubernetes community: not building an isolated solution from scratch, but addressing a long-standing upstream problem that hasn't been fully resolved.

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