AWS Machine LearningLabs
Announcing new ways to customize models with SageMaker AI, without managing GPUs

Companies getting real results from AI aren’t only using foundation models (FMs) off the shelf. They’re customizing open-weight models using post-training techniques such as reinforcement learning.
Read at AWS Machine Learning ↗Related

LabsWrite your own training loop — without managing GPUs — with Amazon SageMaker training session APIs AWS Machine Learning

VoicesWhy AI Compute Comes in Rectangles — Erik Bernhardsson, Modal CEO Latent Space

SiliconHow to Read Data into GPU Memory in Python with NVIDIA GPUDirect Storage NVIDIA Technical Blog

SiliconRunning Frontier-Class AI Models Across 8 NVIDIA DGX Spark Nodes NVIDIA Technical Blog

GitHubGoogle and AWS open new paths for PyTorch beyond Nvidia The New Stack
