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

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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。

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Tom's HardwareSilicon

Benchmarking Qwen 3.8 27B on RTX 5090 and beyond — VRAM capacity alone can't overcome severe software and inference engine bottlenecks

September 8

Alibaba’s Qwen 3.8 27B open-weight AI model came out a couple of weeks ago, and it immediately created a wave of hype among local AI enthusiasts thanks to its impressive intelligence benchmark results for a model of its

Models & releases Research

Read at Tom's Hardware ↗

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Voices[AINews] Poolside gets $12B reverse-execuhire to NVIDIA; founders stay for $1B, employees go for $6B, Infraco scaling to 7GW neocloud Latent Space

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Benchmarking Qwen 3.8 27B on RTX 5090 and beyond — VRAM capacity alone can't overcome severe software and inference engine bottlenecks

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