Source commit: b02deb5
Have you ever had this experience: while learning about Transformers, you suddenly hit the term "attention mechanism" and have to jump away to search what attention is; while learning BERT, you encounter "Encoder-Only" and have to look up what an encoder is. Knowledge should be connected, yet it is often fragmented across isolated documents.
With commit b02deb5, Easy AI did something that looks simple but has far-reaching impact: it built a cross-link network between 9 existing knowledge sites.
What Is Cross-Linking?
Each knowledge site is no longer an isolated island but a node on the internet. When you are learning BERT, the site directly tells you:
> It's smoother to read the "Transformer" site first. BERT uses the left half of the Transformer (the Encoder, read-only), and these components are all parts taken from the Transformer.
A button is attached—one click takes you to the Transformer site.
When you read "671B parameters / 37B activated" on the DeepSeek R1 page, it explains:
> 671B is the total weight, but only 37B is actually used each time a token is generated (via MoE, which wakes up only part of the network each time—see the "MoE" site for details).
Again with a jump button.
Knowledge Sites Covered by the Cross-Link Upgrade
This upgrade covers 9 existing knowledge sites, each with deepened content and cross-link conversion:
- BERT: Added Encoder-Only concept explanation; new Transformer cross-link card
- DeepSeek R1: Strengthened explanation of RL-based training; new LLM/MoE/RLHF cross-links
- GPT: Added Few-Shot and Chain-of-Thought concepts
- Llama: Expanded per-version innovations; strengthened license explanations
- MoE: Improved visualization of expert routing and load balancing
- Multimodal: Enhanced explanation of fusion mechanisms
- T5: Added Encoder-Decoder pipeline details
- Transformer: Substantially expanded Attention, QKV, and modern applications sections
- NLP: Improved tokenizer and pipeline difference explanations
- Claude Opus 4.8 launch experience
- OpenAI gpt-5.5 instant update
- Step 3.7 Flash release
- Google Gemini Managed Agents launch
- Plus multiple advances in model quantization, deployment, and tooling
Cross-Linking Is Not Adding Links—It Is Building a Road Network
Adding a few hyperlinks is not cross-linking. Easy AI's approach goes deeper:
1. Insert cross-link cards at key concepts: not a small line of text, but a full card with an icon and description, telling you why to jump over and what to look at.
2. Explain the meaning of cross-site references: instead of dropping a term for you to look up yourself, it explains the term's meaning in context and notes where the detailed explanation lives.
3. Unified visual style: all cross-link cards use a consistent butter-colored background, rounded corners, shadows, and icons, so users instantly recognize an entry point for further learning.
Why This Matters
Learning is never linear. While learning A you encounter B, and learning B reminds you of C. A good knowledge system should embrace this jumping nature rather than fight it.
The cross-link network turns Easy AI from a knowledge exhibition hall into a knowledge exploration map. You don't need to know the learning path in advance—start from any point of interest and wander naturally between related concepts via the links.
This follows the same philosophy as Wikipedia, but is better suited for AI learning: Wikipedia links tend to be overly academic, while Easy AI's cross-link cards explain concept relationships in plain language, so readers without background can understand why they need to read something.
The Other Side of the Update: Daily News Data
Beyond the cross-linking, this commit also added AI daily news data for 2026-05-30, covering:
> Visit Easy AI to experience the cross-linked knowledge sites: https://mmh1.top
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> This article is an interpretation of Easy AI project commit b02deb5.