How Heisenberg's CPU Network Decentralizes AI (and Who Really Controls It)

Who controls the future of AI—Big Tech, or all of us? Mori Zihayat from the Heisenberg Network makes a powerful case for decentralizing AI, moving beyond just compute to the personalization and power layers. Discover how a CPU-first network can provide AI agents with real-time context, all without relying on billion-dollar data centers.

This is a must-watch for anyone interested in the future of artificial intelligence, web3, and building a more human-centered digital world.

💡 You’ll Learn:
- Why centralizing AI power is the real risk (and how to decentralize the personalization layer).
- How CPU nodes and community-driven pipelines work (the “prompt-to-process” idea).
- The four-part map for building decentralized AI: Data → Processing → Training → Agents.
- What truly motivates this push for decentralization: accessibility for all.
- How you can get involved and potentially earn rewards by contributing your CPU.

🔗 Links & Resources:
• Heisenberg Network: https://www.heisenberg.so
• Mori Zihayat on LinkedIn: https://www.linkedin.com/in/morteza-zihayat/

Connect with The Weird Canadian:
📧 https://stan.store/The_Weird_Canadian

💬 Timestamps:
00:00 - Do We Need Data Centers for AI?
00:55 - What is Human-Centered AI?
03:55 - The Origins of Decentralized Power vs. Compute
05:50 - Decentralizing the AI Personalization Layer
07:15 - Data Centers vs. Distributed CPU Compute
09:45 - Risks & Security of a Decentralized Network
15:45 - Why Accessibility is the True Motivator
28:20 - Will AI Cause Job Loss or Create New Opportunities?
35:50 - How to Build Decentralized AI Solutions
42:45 - Heisenberg’s Vision: Agent-as-a-Service
45:55 - Why CPU is Better Than GPU for Decentralized AI

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#AI #Decentralization #HumanCenteredAI #HeisenbergNetwork #Web3 #CPUPower #podmatch