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Fourth-generation flagship release from Deepseek (April 24, 2026). Two open-weight variants — V4-Pro (1.6T total / 49B active parameters) and V4-Flash (284B total / 13B active) — both built on a MoE) architecture, ship with a 1M-token Context Window by default, and fold what was the separate R reaso
DESIGN.md is an open Apache-2.0 format specification from Google Labs for describing a design system to coding agents in a single, version-controllable file. It pairs machine-readable design tokens in YAML front matter with human-readable design rationale in markdown prose — so an LLM) can apply vis
A plugin that turns a structured Obsidian note tree into an actual book; exported to EPUB and PDF.
A family of attention mechanisms that compute interactions between only a subset of token pairs instead of every pair, breaking the O(n²) cost of full self-attention. The dense attention used in vanilla Transformers forces every token to attend to every other token; sparse attention restricts that i
AI models whose trained weights are publicly released, allowing anyone to download, run, fine-tune, and deploy them. "Open weight" is more precise than "open source" because most releases don't include training code or data.
Granite 4.1 is IBM's open-weight LLM) family released in April 2026 under the Apache 2.0 License. It is a deliberate retreat from the MoE) direction taken by Granite 4.0, returning to a decoder-only dense transformer design with no expert routing, no sparse layers, and no extended reasoning chains.
#pillar-tools-and-systems
Book Exporter turns a structured Obsidian note tree into a real book; one manifest note, one command, EPUB and PDF out the other side via Pandoc.
#pillar-creator-systems
Most people send sensitive prompts to AI tools without knowing where that data ends up. Here's what really happens, why the rules differ wildly per tier, and what to pay attention to.
AI
Three weeks of shipping: 3 open-source AI Skills (Garmin, arXiv, Scholar); two new Obsidian plugins (Hidden Folders, Graph Explorer); the OSK v4 runway; a News Flash page on my blog; updated Knowii pricing; and the Kimi K2.6 + Qwen + Gemma 4 local AI wave.
Kimi K2.6 is an open-source LLM) from Moonshot AI, released in April 2026. It is the successor to Kimi K2.5 and is positioned as an open-weight frontier model for long-horizon, agent-style coding and tool use, competing directly with Claude Opus 4.7, GPT-5.4, and Gemini 3 on coding and agentic bench
🏠 User Guide / Systems / LLM Wiki System
April 2026 has been a big month for open-weight AI, and it's not over yet. Three releases landed back-to-back, and together they show that the AI models you can run yourself are getting MUCH more capable, MUCH faster than most people expected.
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