While much attention is focused on artificial intelligence (AI) training of large, complex models, the reality for most organizations is different. Instead of building models from scratch, many companies are leaning towards using pre-trained models and fine-tuning them for specific tasks.

These companies focus the majority of their resources and operational effort on serving the models at scale for real-world applications. This is where the challenge of inferencing at scale becomes paramount.

At the AI Infrastructure Field Day in April, Google offered a deeper look at how its new GKE Inference Gateway helps organizations optimize their inference workloads at scale.

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