Orchestrating ML/AI workloads with TPUs on GKE

Apr 9, 2026Channel
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Published3 months ago
Duration51:47
Video IDcoP5_SmE4AI
Languageen-US
CategoryScience & Technology
PrivacyPublic
Made for KidsNo
Video TypeRegular Video

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Views1.3K
Likes28
Comments2
Engagement Rate2.37%
Likes per 100 views2.21
Comments per 1K views1.58

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Google AI Hypercomputer → https://goo.gle/3ObrQLK GKE for AI/ML inference → https://goo.gle/4cg4k8y [Tutorial] Fine tune a LLM using TPUs on GKE → https://goo.gle/48hT4Hu Tensor Processing Units (TPUs) are now in their 7th generation. They allow machine learning workloads to reach massive scale, especially when running on Google Kubernetes Engine (GKE). But how does that work, and what do you need to know in order to run TPUs on GKE successfully? Join Yufeng Guo as he sits down with Kavitha Gowda, the product manager of TPUs on GKE, to get into the details of how to scale TPU workloads on GKE. Speakers: Yufeng Guo, Kavitha Gowda Products Mentioned: Google Kubernetes Engine, Cloud Tensor Processing Units, AI Hypercomputer

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