Spatial Web + Active Inference: Beyond LLMs | Dan Mapes
No Way Out
What Is a World Model?
Dan clarifies world models as evolving, embodied understandings at varying scopes, distinct from LLM text-only models.
đ **Spatial Web + Active Inference = Intelligent Planet**
Dan Mapes (Versus AI, Spatial Web Foundation) joins *No Way Out* to **destroy LLM myths** and reveal **FEP-powered 3D web**
What if the web didnât just host pagesâit hosted intelligence? We sit down with Dan Mapes, director of the Spatial Web Foundation and co-founder of Verses AI, to unpack how a shared protocol, digital twins, and Active Inference could turn todayâs internet into a living, learning fabric that understands space, time, and context. Instead of one giant model, imagine thousands of expert AIsâcardiology, ports, power gridsâeach built by domain leaders, all interoperable and discoverable like websites. Thatâs not hype; itâs a shift from a 2D information web to a 3D web of intelligence.
We explore Karl Friston's Free Energy Principle and Active Inference with real-world stakes: energy efficiency closer to brains than data centers, autonomous decisions that donât break when the world changes, and robotics that adapt without million-dollar pre-training. Dan explains how world models evolve through sensing and action, why protocols matter more than monoliths, and how decentralization enables hyperâlocal solutions that still plug into a global network. From OODA to flow, meditation to geometry, we connect the mental models behind invention with the engineering that makes it durable.
The implications are huge: smart cities that coordinate in real time, supply chains that sense and respond, and a path from LLM content tools to embodied, autonomous systems. We also talk culture and economicsâwhy abundance eases control, how institutions adapt like they did after the printing press, and why this next era could make us more human, not less. If youâre a founder, policymaker, or systems leader, this is a blueprint for building actionable intelligenceâstarting with small, truthful models that learn every day.
If this conversation sparks ideas, follow and share the show, leave a review, and tell us where you want intelligence to plug int
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