Google Cloud makes Cloud Pathways distributed ML runtime generally available on GKE

[Google Cloud] Google Cloud said its Cloud Pathways distributed machine-learning runtime for massive accelerator fleets is now generally available on Google Kubernetes Engine (GKE), positioning it as a core runtime pillar of the Google Cloud AI Hypercomputer. Pathways was originally engineered by Google DeepMind to train and serve Google's frontier models, including Gemini. According to Google Cloud, leading AI companies and global enterprises processed more than 130 million Cloud TPU chip-hours using Pathways on GKE over the last 90 days, across a broad range of TPU generations. Cloud Pathways uses a single-controller architecture built on the open-source Interim Framework Runtime (IFRT) and offers colocated Python sidecars, elastic fault-tolerant training, an interactive mode and a Shared Pathways Service. Google Cloud also announced a Preview integration with Cluster Director to extend Cloud Pathways to Slurm clusters, supporting unified multi-slice JAX execution, elastic training and interactive notebooks.