👎 Most talking AI models break when you add multiple people to a conversation.

✅ MultiTalk shows a lot of potential to solve this, using a new approach that correctly binds multi-stream audio to specific characters.

Github repo 👇

I just discovered MAGREF.

This fine-tuned Wan 2.1 model keeps faces and objects consistent across video scenes.

Single subject or multi-reference mode - both work surprisingly well.

Big fan of Wan2GP by DeepBeepMeep for running video generation on low-end GPUs. The name might be misleading, but it actually supports multiple open-source models including Wan (plus its derivatives), Hunyuan Video, and LTV Video.

Link to the repo, if you are interested 👇

5. The magic config
- Add to `~/Library/Application\ Support/Claude/claude_desktop_config.json` (or where you have Claude Desktop installed)

pastebin.com/rY62GMZy

🔥 5-min guide: Build your personal AI research assistant that automatically searches & saves everything to Notion. From research to organized notes, automatically. Here's how → 🧵 #ResearchTools

5. E - EXPRESS 🚀
Turn knowledge into action:
- Train custom AI models
- Create automation workflows
- Share insights with your audience

I've built a few personal automation tools using this pipeline!

4. D - DISTILL 🌟
The magic happens here:
- Progressive summarization
- Extract core ideas
- Find key patterns

This creates clean, structured data that LLMs can learn from effectively.

3. O - ORGANIZE 🗂️
PARA system is key here:
- Projects (active)
- Areas (ongoing)
- Resources (reference)
- Archives (inactive)

This structure helps both humans AND machines understand context better!

2. C - CAPTURE 📥
First, systematically collect valuable information:
- Save resonating content
- Store meaningful data
- Focus on actionable insights

Pro tip: I use @notion.com API to automate this, feeding directly into my AI pipeline

Supercharge your AI systems with the CODE method 🧠

How I turned Tiago Forte's Second Brain framework into a powerful data pipeline for AI automation. 🧵👇