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Ahead of AI

20 stories

How Claude Watermarks AI-Generated Text

Ahead of AIVoicesHow Claude Watermarks AI-Generated Text A 48-minute video walkthrough of token sampling, watermark detection, and removal

Building an AI Text Detector From Scratch

Ahead of AIVoicesBuilding an AI Text Detector From Scratch An End-to-End Project With Dataset Construction, Model Training, Local Deployment, and RLVR

Controlling Reasoning Effort in LLMs

Ahead of AIVoicesControlling Reasoning Effort in LLMs How LLMs Learn Low-, Medium-, and High-Effort Reasoning Modes

Using Local Coding Agents

Ahead of AIVoicesUsing Local Coding Agents Using Open-Weight Models in Local Coding Harnesses as an Alternative to Claude Code and Codex Subscriptions

LLM Research Papers: The 2026 List (January to May)

Ahead of AIVoicesLLM Research Papers: The 2026 List (January to May) A curated roundup of notable LLM research papers that came out this year

Recent Developments in LLM Architectures: KV Sharing, mHC, and Compressed Attention

Ahead of AIVoicesRecent Developments in LLM Architectures: KV Sharing, mHC, and Compressed Attention From Gemma 4 to DeepSeek V4, How New Open-Weight LLMs Are Reducing Long-Context Costs

My Workflow for Understanding LLM Architectures

Ahead of AIVoicesMy Workflow for Understanding LLM Architectures A learning-oriented workflow for understanding new open-weight model releases

Components of A Coding Agent

Ahead of AIVoicesComponents of A Coding Agent How coding agents use tools, memory, and repo context to make LLMs work better in practice

A Visual Guide to Attention Variants in Modern LLMs

Ahead of AIVoicesA Visual Guide to Attention Variants in Modern LLMs From MHA and GQA to MLA, sparse attention, and hybrid architectures

A Dream of Spring for Open-Weight LLMs: 10 Architectures from Jan-Feb 2026

Ahead of AIVoicesA Dream of Spring for Open-Weight LLMs: 10 Architectures from Jan-Feb 2026 A Round Up And Comparison of 10 Open-Weight LLM Releases in Spring 2026

Categories of Inference-Time Scaling for Improved LLM Reasoning

Ahead of AIVoicesCategories of Inference-Time Scaling for Improved LLM Reasoning And an Overview of Recent Inference-Scaling Papers

The State Of LLMs 2025: Progress, Problems, and Predictions

Ahead of AIVoicesThe State Of LLMs 2025: Progress, Problems, and Predictions A 2025 review of large language models, from DeepSeek R1 and RLVR to inference-time scaling, benchmarks, architectures, and predictions for 2026.

LLM Research Papers: The 2025 List (July to December)

Ahead of AIVoicesLLM Research Papers: The 2025 List (July to December) In June, I shared a bonus article with my curated and bookmarked research paper lists to the paid subscribers who make this Substack possible.

From DeepSeek V3 to V3.2: Architecture, Sparse Attention, and RL Updates

Ahead of AIVoicesFrom DeepSeek V3 to V3.2: Architecture, Sparse Attention, and RL Updates Understanding How DeepSeek's Flagship Open-Weight Models Evolved

Beyond Standard LLMs

Ahead of AIVoicesBeyond Standard LLMs Linear Attention Hybrids, Text Diffusion, Code World Models, and Small Recursive Transformers

Understanding the 4 Main Approaches to LLM Evaluation (From Scratch)

Ahead of AIVoicesUnderstanding the 4 Main Approaches to LLM Evaluation (From Scratch) Multiple-Choice Benchmarks, Verifiers, Leaderboards, and LLM Judges with Code Examples

Understanding and Implementing Qwen3 From Scratch

Ahead of AIVoicesUnderstanding and Implementing Qwen3 From Scratch A Detailed Look at One of the Leading Open-Source LLMs

From GPT-2 to gpt-oss: Analyzing the Architectural Advances

Ahead of AIVoicesFrom GPT-2 to gpt-oss: Analyzing the Architectural Advances And How They Stack Up Against Qwen3

The Big LLM Architecture Comparison

Ahead of AIVoicesThe Big LLM Architecture Comparison From DeepSeek-V3 to Kimi K2: A Look At Modern LLM Architecture Design

LLM Research Papers: The 2025 List (January to June)

Ahead of AIVoicesLLM Research Papers: The 2025 List (January to June) A topic-organized collection of 200+ LLM research papers from 2025

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。