Google has introduced TPU 8t and TPU 8i, distinct chips designed for training and inference respectively, reflecting a divergence in workload demands as models grow more complex. This split addresses the increasing pressure on memory bandwidth and synchronization efficiency in agentic workflows, crucial for developers working with large-scale AI models.
Read the full article at The New Stack
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