Reproducing OLMo 3 7B on TPUs reveals hidden data loader bugs
A Google case study reproduces AI2's OLMo 3 model on TPUs, matching performance metrics while uncovering critical data sharding errors that masked memorization as improvement.
Building with AI
RAG, evaluations, inference, fine-tuning and shipping LLM features to production.
Google demonstrates autonomous LLM fine-tuning loops on TPUs
Google Developers Blog details autofinetune, an agent-driven system that automates hyperparameter tuning for SFT and RL post-training on Cloud TPUs.
Optimizing long-context embedding inference on Cloud TPU with vLLM
Google details how native TPU support in vLLM enables elastic scaling and high-precision embedding inference for Qwen3 models.
Handling GPU failures in Kubernetes for AI workloads
Kubernetes lacks native support for partial device failures, forcing engineers to build custom remediation logic for expensive AI and ML training jobs.
Kubernetes introduces Gateway API extension for LLM inference routing
The Kubernetes project released the Gateway API Inference Extension to standardize routing for generative AI workloads, reducing latency and improving GPU utilization.
