Spatial Web AI Podcast Exclusive Look at CL1: One-on-One with Cortical Labs’ Chief Scientist
Apr 16, 2025
In a captivating conversation, Brett Kagan, Chief Scientist at Cortical Labs, discusses the revolutionary CL1 system, which merges human neurons with silicon computing for synthetic biological intelligence. He shares insights from the DishBrain experiment, which demonstrated neuron-based gameplay and validated Dr. Friston's Free Energy Principle. The podcast delves into the energy efficiency of biological intelligence compared to traditional AI, the ethical implications of using human neurons in research, and the vast potential applications for drug discovery and personalized medicine.
AI Snips
Chapters
Transcript
Episode notes
Biological Cells Define Intelligence
- True intelligence derives from biological brain cells rather than silicon models.
- Leveraging live neurons could create more powerful processors than traditional silicon computing.
Electricity Bridges Neurons and Silicon
- The shared communication method between neurons and silicon is electricity, forming a bridge.
- Shaping this electrical language is key to interacting with neurons and achieving useful hybrid computing.
Neurons Learn by Minimizing Surprise
- Neurons learn through a closed-loop system minimizing surprise, as validated by the free energy principle.
- Random unpredictable inputs cause neurons to adapt behavior to reduce errors, improving task performance like playing Pong.