Virtual Machine News Platform
Multiple teams within the same company increasingly need shared access to expensive GPU clusters for their generative AI operations, while…
We recently introduced the ability to create and manage Amazon SageMaker Spaces on Amazon SageMaker HyperPod EKS clusters directly from…
Amazon SageMaker HyperPod gives machine learning (ML) teams access to large pools of accelerated compute for training and fine-tuning models.…
Reinforcement learning (RL) post-training is becoming a standard step in building capable language model agents. Models learn to reason and…
Today, we are announcing new Ray capabilities on Amazon SageMaker HyperPod that integrate Ray with the HyperPod purpose-built infrastructure for…
Running large language model (LLM) inference at scale typically forces a KV cache trade-off: you either pay for oversized GPU…
Amazon SageMaker HyperPod offers an end-to-end experience supporting the full lifecycle of AI development—from interactive experimentation and training to inference…
This post is cowritten with Altay Sansal and Alejandro Valenciano from TGS. TGS, a geoscience data provider for the energy…
This blog post was co-authored with Johannes Maunz, Tobias Bösch Borgards, Aleksander Cisłak, and Bartłomiej Gralewicz from Hexagon. Hexagon is…
Training and deploying large AI models requires advanced distributed computing capabilities, but managing these distributed systems shouldn’t be complex for…
