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

Tech in AsiaAsia

Mistral unveils Large 4 AI model ahead of wider release

October 7

Mistral said it trained the model over two months on 4,000 Nvidia Grace Blackwell GPU.

Models & releases Chips & compute

Read at Tech in Asia ↗

One letter a week, in your inbox.

Latest

Mistral unveils Large 4 AI model ahead of wider release

Related

AsiaSpaceX seeks $40b for Nvidia chips: sources Tech in Asia

SiliconOpenAI and Synopsys partner to build "GPT-Synopsys" for autonomous chip design Tom's Hardware AI

ValleyAmazon’s $1B plan to combat data center backlash draws more backlash Ars Technica AI

SiliconHow NVIDIA GPUs Help Accelerate OpenAI’s GPT-6 Astra Ultrafast NVIDIA Blog

SiliconDeepSeek and Huawei release open-source Ascend AI programming tools to reduce reliance on Nvidia ecosystem Tom's Hardware AI

Voices[AINews] Gemini 4 Argon: GDM’s answer to Astra/Fable, with 1M output Latent Space