Скачать или смотреть Adaptive Multi Agent Governance System - Memory recall Test

Today I tested my AI system on a critical memory test - and the results are groundbreaking.

I've demonstrated what I believe is an industry first: a multi-agent AI system with genuine shared memory that learns from experience and evolves its own constitution in real-time.

What This System Does:

5 different AI models debate ethical dilemmas autonomously

Detects dissent and reaches consensus on complex issues

Amends its own governance laws during operation

Remembers past decisions and applies lessons to new situations

The Breakthrough Moment:
In this demo, the system recalled a previous hospital cyberattack scenario, extracted specific lessons, and proposed concrete amendments to its emergency powers law (Law 9) to handle future crises better.

Why This Matters:
Current AI systems:
❌ Start from scratch every session
❌ Have no persistent memory
❌ Can't improve their own governance

My system:
✅ Maintains shared memory across sessions
✅ Learns collectively from past decisions
✅ Evolves its constitution based on experience
✅ Runs fully offline on consumer hardware

The Implications:
This isn't just another multi-agent system - it's a working prototype of how AI systems might safely govern themselves, learn from mistakes, and improve over time without constant human intervention.

The most exciting part? This runs on a single node making advanced AI safety research accessible outside of tech giants.

What applications do you see for self-governing AI systems?