AI 快讯

2ヶ月経ってるけど、これを作ると入社した〜という感じがする！！ 🏋️＋👶＋🍕＝ワシ ht

When I saw our team's evals of Kimi 2.6, I thought "ok, things are gonna get interesting now". This is the first open-weight model that plays like a top-class agentic model. Watching it go through ambiguous and meticulous chained tool work successfully puts it squarely in the

Kimi K2.6 just landed in @NotionHQ. Open‑weight, but absolutely a heavyweight. Take it for a drive! 🏎️

SF builders: Join us for two days of hands-on building on our new Developer Platform. Sync any data source into Notion, give your agent any tool, and trigger workflows from anywhere. No servers, no infra. Just a CLI and your ideas. Space is limited. Apply here:

I've always loved the idea of @NotionHQ, but up until recently, never loved using it. All that's changed now, and this article explains why, but it's everything else it explains that makes this such an important read. What stuck out to me was the "think together" video vignette.

We're launching the Anthropic STEM Fellows Program. AI will accelerate progress in science and engineering. We're looking for experts across these fields to work alongside our research teams on specific projects over a few months. Learn more and apply:

We're expanding our collaboration with Amazon to secure up to 5 gigawatts of compute for training and deploying Claude. Capacity begins coming online this quarter, with nearly 1 gigawatt expected by the end of 2026.

Introducing Claude Opus 4.7, our most capable Opus model yet. It handles long-running tasks with more rigor, follows instructions more precisely, and verifies its own outputs before reporting back. You can hand off your hardest work with less supervision.

Research we co-authored on subliminal learning—how LLMs can pass on traits like preferences or misalignment through hidden signals in data—was published today in @Nature. Read the paper:

New Anthropic Fellows research: developing an Automated Alignment Researcher. We ran an experiment to learn whether Claude Opus 4.6 could accelerate research on a key alignment problem: using a weak AI model to supervise the training of a stronger one.