AWS sells out cloud capacity through 2027 as AI demand grows
AWS 的算力直接订到 2027 年了，想租 GPU 跑模型的朋友可以看看它给 Bedrock 和 EC2 留了哪些余量。
AWS 的云算力已被预订至 2027 年，反映 AI 训练与推理需求持续走高。AWS 同时保留了部分 2027 年产能，供按需客户以及 Bedrock、EC2 等服务使用。算力紧张意味着新客户获取大规模 GPU 资源的成本和门槛都在上升。
AWS sells out cloud capacity through 2027 as AI demand grows
AWS is holding back some 2027 capacity for on-demand customers and services like Bedrock and EC2.
贾西原话说 2027 年 AWS 算力都卖光了，2026 年砸 2200 亿美元扩容，想了解云厂商抢算力有多疯的可以看看。
拜耳用 Amazon Bedrock AgentCore 搭了个多智能体引擎，育种人员直接用自然语言查数据，文章还拆了 5 个关键设计决策，做企业级 Agent 的可以抄作业。
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.
Priming makes hybrid architectures practical by skipping full pretraining, which could shift how teams convert existing checkpoints into cheaper-to-serve models. Engineers deploying 8B-32B scale models can use the released weights to cut inference memory and cost immediately. It competes with from-scratch hybrid efforts like those from other labs at a fraction of the compute spend.
做模型微调的朋友可以看看：SageMaker AI 新出的训练会话让你自己写 RL 训练循环，GPU 那摊事 AWS 全包了。
