From e37b6e63b306f7bfeb0e59bdbb253fa19c7cd62f Mon Sep 17 00:00:00 2001 From: Zach Rossmiller Date: Mon, 27 Jul 2026 09:06:59 -0600 Subject: [PATCH] curate: 2 new terms (Kimi K3, AI Browser) --- terms/ai-browser.json | 10 ++++++++++ terms/kimi-k3.json | 10 ++++++++++ 2 files changed, 20 insertions(+) create mode 100644 terms/ai-browser.json create mode 100644 terms/kimi-k3.json diff --git a/terms/ai-browser.json b/terms/ai-browser.json new file mode 100644 index 0000000..e8582f8 --- /dev/null +++ b/terms/ai-browser.json @@ -0,0 +1,10 @@ +{ + "slug": "ai-browser", + "term": "AI Browser", + "acronym": null, + "category": "Patterns", + "short": "A web browser with an AI agent built in that can read pages and act on them for you.", + "definition": "An AI browser is a web browser built around an AI assistant that can see the page you're on, answer questions about it, and carry out multi-step actions like filling out forms, comparing prices, or booking something, instead of just displaying pages for you to operate by hand. Several consumer browsers released agent modes like this, alongside open-source frameworks that add similar abilities to ordinary browsers. Because the assistant can act on logged-in sites, these browsers face real security challenges, especially prompt injection, where a malicious page tricks the assistant into acting against the user's wishes.", + "example": null, + "related": ["computer-use", "agent", "prompt-injection", "browsergym"] +} diff --git a/terms/kimi-k3.json b/terms/kimi-k3.json new file mode 100644 index 0000000..f8de8c5 --- /dev/null +++ b/terms/kimi-k3.json @@ -0,0 +1,10 @@ +{ + "slug": "kimi-k3", + "term": "Kimi K3", + "acronym": null, + "category": "Models & Products", + "short": "Moonshot AI's large open-weight model, released July 2026 and notable for strong coding and agentic performance.", + "definition": "Kimi K3 is a large open-weight model from the Chinese AI company Moonshot AI, released in July 2026 as one of the biggest open-weight models available at the time. Like other frontier-scale systems, it uses a mixture-of-experts design that activates only a fraction of its many specialized sub-networks for each request, keeping it efficient to run despite its size. It drew wide attention for topping coding leaderboards and for strong agentic performance — carrying out multi-step tasks with tools — continuing Moonshot's focus on long-context handling from earlier Kimi releases.", + "example": null, + "related": ["kimi", "moonshot-ai", "open-weights", "moe", "deepseek-v4"] +}