The name is the button.

An agent writes the code now, and a human thumb hovers over Accept all a hundred times a day. The honest question of this decade is what, exactly, you just accepted. So I read the diff.

Eight years as a backend engineer in Stockholm, back in Tokyo since 2023, and I still ship something small most nights, usually badly. My one rule: the only real review of a model is the thing you built with it. That is why there is no leaderboard on this site.

Around a hundred and forty sources come through — the labs' own posts, the papers, the tools, the runtimes and languages nobody is watching yet, the chip under the demo, and the newsletters people actually forward. What is moving gets counted so the week reads at a glance, and every few days I explain one mechanism in plain words.

A story here is a headline, a short excerpt, one image and the link to whoever wrote it. We never reproduce the post; the images belong to their authors. A post written in Japanese appears in Japanese, exactly as it was published, and the link goes to the original.

— Yuki Halvorsen, Tokyo

← Accept All Archive

AWS Machine LearningLabs

Distributed training with Ray Train DLCs and EFA on EKS

10.28

What usually stops PyTorch training from scaling out to a cluster is the container, not the model code.

Read at AWS Machine Learning ↗

One letter a week, starting soon.

Latest

Distributed training with Ray Train DLCs and EFA on EKS

More from AWS Machine Learning on Accept All

LabsAccelerating software delivery with agentic QA automation using Amazon Nova Act – Part 3 AWS Machine Learning

LabsAWS named a Leader in the 2026 Gartner Magic Quadrant for Contact Center as a Service AWS Machine Learning

LabsAnnouncing SOCI-indexed images for faster SageMaker AI jobs AWS Machine Learning

LabsFix evaluation bias to unlock better models on Amazon Bedrock AWS Machine Learning

LabsExowatt beats frontier models on accuracy with SageMaker serverless model customization AWS Machine Learning

LabsFleet-wide computer vision lifecycle at the edge with SageMaker SDK v3 AWS Machine Learning