Latest

On the calendar

予定 · Conferences and launch events, this week's stories from each corner of the industry, and what its press is covering — in English

On view

This week, from that corner the newest stories from the corner of the industry you picked

The wire their own posts, translated

How code moves in 2026 from the industry's own reports

Sources

Fetched every three hours, linked to the original

About

Accept All is a magazine, a radar and a diary about artificial intelligence and the craft of code — read from Tokyo, for people who build.

The name is the button. Code is written by agents now and reviewed by a human thumb that hovers over Accept all a hundred times a day; the whole question of this decade is what, exactly, you just accepted. So we read the diff. A magazine, because every week one model, one tool or one idea is worth reading about slowly. A radar, because we count what the labs, the Valley, GitHub and the chip makers are talking about — releases, agents, open weights, compute, funding, rules — and show it as it moves. A diary, because a seal is set each day in that day's colour, and the days add up.

We read the research labs' own posts, the American and European tech press, the Japanese and Chinese developer sites and the newsletters people actually forward, and bring it together in English and Japanese. Everything here links back to the people who wrote it; the images belong to their authors.

Accept All will keep changing. New sources, new signals, new ways of looking — a little better each week, never finished. If something here made you open a terminal, that is enough.

Thank you for reading. ありがとうございます。

← Accept All Archive

AWS Machine LearningLabs

Customizing your knowledge base on Amazon Bedrock for large and complex documents using Amazon Textract

September 4

Learn how to customize an Amazon Bedrock knowledge base for large, complex documents by combining the high-accuracy text extraction of Amazon Textract with the generative AI of Amazon Bedrock. This post shows how to inge

Amazon Bedrock Amazon Textract Intermediate (200)Technical How-to

Read at AWS Machine Learning ↗

Latest

Customizing your knowledge base on Amazon Bedrock for large and complex documents using Amazon Textract

Related

LabsTokenomics at scale: How Jamf built real-time spend enforcement for Amazon Bedrock AWS Machine Learning

LabsFrom theory to delivery: How Atos upskilled 400 engineers in agentic AI AWS Machine Learning

LabsIntroducing Claude Fable 5.1 on AWS AWS Machine Learning

LabsTrinity: Agentic AI-powered transition planning for students with disabilities AWS Machine Learning

LabsFrom code to diagrams: Agentic architecture documentation with Amazon Bedrock AgentCore AWS Machine Learning

LabsHow an AWS team detects dashboard content failures at scale using Amazon Bedrock AWS Machine Learning