对于依赖PyTorch进行大规模AI训练的团队，该方案提供了零代码改动的性能提升路径，验证了存储系统优化对训练效率的显著影响。
Google Cloud推出新集成方案，通过fsspec接口将Rapid Storage与PyTorch直连，利用Colossus架构和双向gRPC流，实现最高15 TiB/s聚合吞吐量并显著降低延迟。开发者只需更新存储桶类型，无需修改代码即可使训练总时间缩短23%。该方案旨在消除AI训练中的数据加载瓶颈，提升大规模分布式训练效率。
PyTorch 官方在大会上办了 PTCA 认证考前培训，NVIDIA 讲师带练 GPU 实操，想考 PyTorch 认证的可以看下。
The office hours are a direct channel to influence DeepSpeed's Q4 priorities, which is rare for a framework of this scale. Practitioners benchmarking training frameworks should attend to question the parallelism results against their own workloads, since the claims of matching state-of-the-art frameworks were made only on selected workloads. The benchmark comparisons against rival frameworks set the baseline for distributed training choices going into 2027.
有人破解了 3090 被锁的算力，同样 360W 功耗从 75 跑到 135 TFLOPS，4090 分支项目直接翻倍，搞 AI 训练的可以看看
有人钻了显卡固件的漏洞，3090 不超功耗直接多出 80% 算力，跑 AI 的老卡党快看。
如果你在 AWS 上用 PyTorch 训练模型，现在可以直接跑在 Trainium 芯片上，不用换框架，省下不少算力成本。
Open-sourcing the Trainium backend lowers the barrier for teams to run PyTorch workloads on AWS's in-house silicon without vendor-specific rewrites. Teams benchmarking inference costs against NVIDIA GPUs can now inspect and extend the translation layer directly. The agent-driven validation approach across hundreds of thousands of models is also a reference point for automated compatibility testing.
