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1/2PyTorch now integrates with Google Colossus via GCSFS and fsspec, offering up to 15 TiB/s throughput and reduced latency. This change speeds up AI training time by 23% with no code changes required, beyond updating the storage bucket type. (1/2)
2/2It matters for engineers training large AI models, as it reduces bottlenecks without additional development effort. (2/2)
โก PyTorch now integrates with Google Colossus via GCSFS and fsspec, offering up to 15 TiB/s throughput and reduced latency. This change speeds up AI training time by 23% with no code changes required...
developers.googleblog.com/speeding-up-ai-bringing-google-colossus-to
PyTorch now integrates with Google Colossus via GCSFS and fsspec, offering up to 15 TiB/s throughput and reduced latency. This change speeds up AI training time by 23% with no code changes required, beyond updating the storage bucket type. It matters for engineers training large AI models, as it reduces bottlenecks without additional development effort.
Practical takeaway: review whether this affects current AI/mobile build, integration, or release workflows.
โก Speeding Up AI: Bringing Google Colossus to PyTorch via GCSFS and Rapid Bucket
Speeding Up AI: Bringing Google Colossus to PyTorch via GCSFS and Rapid Bucket
PyTorch now integrates with Google Colossus via GCSFS and fsspec, offering up to 15 TiB/s throughput and reduced latency. This change speeds up AI training time by 23% with no code changes required, beyond updating the storage bucket type. It matters for engineers training large AI models, as it reduces bottlenecks without additional development effort.
#Android #Kotlin #KMP #MobileDev #iOS
developers.googleblog.com/speeding-up-ai-bringing-google-colossus-to